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Merge pull request #7 from Doctorado-ML:add_excel_belist

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Add excel output of reports of be_list
This commit is contained in:
Ricardo Montañana Gómez
2022-11-18 23:37:17 +01:00
committed by GitHub
parent feea9c542a c8124be119
commit 68d9cb776e
33 changed files with 487 additions and 207 deletions
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3
benchmark/Models.py
View File

@@ -8,7 +8,7 @@ from sklearn.ensemble import (
)
from sklearn.svm import SVC
from stree import Stree
from bayesclass import TAN, KDB
from bayesclass import TAN, KDB, AODE
from wodt import Wodt
from odte import Odte
from xgboost import XGBClassifier
@@ -23,6 +23,7 @@ class Models:
"STree": Stree(random_state=random_state),
"TAN": TAN(random_state=random_state),
"KDB": KDB(k=3),
"AODE": AODE(random_state=random_state),
"Cart": DecisionTreeClassifier(random_state=random_state),
"ExtraTree": ExtraTreeClassifier(random_state=random_state),
"Wodt": Wodt(random_state=random_state),

87
benchmark/Results.py
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@@ -7,6 +7,7 @@ import abc
import shutil
import subprocess
import xlsxwriter
from xlsxwriter.exceptions import DuplicateWorksheetName
import numpy as np
from .Experiments import BestResults
from .Datasets import Datasets
@@ -21,6 +22,10 @@ from .Utils import (
from ._version import __version__
def get_input(is_test):
return "test" if is_test else input()
class BestResultsEver:
def __init__(self):
self.data = {}
@@ -125,7 +130,7 @@ class BaseReport(abc.ABC):
class Report(BaseReport):
header_lengths = [30, 6, 5, 3, 7, 7, 7, 15, 16, 15]
header_lengths = [30, 6, 5, 3, 7, 7, 7, 15, 17, 15]
header_cols = [
"Dataset",
"Sampl.",
@@ -184,7 +189,7 @@ class Report(BaseReport):
)
i += 1
print(
f"{result['time']:9.6f}±{result['time_std']:6.4f} ",
f"{result['time']:10.6f}±{result['time_std']:6.4f} ",
end="",
)
i += 1
@@ -328,7 +333,17 @@ class Excel(BaseReport):
else:
self.book = book
self.close = False
self.sheet = self.book.add_worksheet(self.data["model"])
suffix = ""
num = 1
while True:
try:
self.sheet = self.book.add_worksheet(
self.data["model"] + suffix
)
break
except DuplicateWorksheetName:
num += 1
suffix = str(num)
self.max_hyper_width = 0
self.col_hyperparams = 0
@@ -1341,6 +1356,7 @@ class Summary:
def __init__(self, hidden=False) -> None:
self.results = Files().get_all_results(hidden=hidden)
self.data = []
self.data_filtered = []
self.datasets = {}
self.models = set()
self.hidden = hidden
@@ -1417,13 +1433,14 @@ class Summary:
number=0,
) -> None:
"""Print the list of results"""
data = self.get_results_criteria(
score, model, input_data, sort_key, number
)
if data == []:
if self.data_filtered == []:
self.data_filtered = self.get_results_criteria(
score, model, input_data, sort_key, number
)
if self.data_filtered == []:
raise ValueError(NO_RESULTS)
max_file = max(len(x["file"]) for x in data)
max_title = max(len(x["title"]) for x in data)
max_file = max(len(x["file"]) for x in self.data_filtered)
max_title = max(len(x["title"]) for x in self.data_filtered)
if self.hidden:
color1 = TextColor.GREEN
color2 = TextColor.YELLOW
@@ -1432,10 +1449,11 @@ class Summary:
color2 = TextColor.LINE2
print(color1, end="")
print(
f"{'Date':10s} {'File':{max_file}s} {'Score':8s} {'Time(h)':7s} "
f"{'Title':s}"
f" # {'Date':10s} {'File':{max_file}s} {'Score':8s} "
f"{'Time(h)':7s} {'Title':s}"
)
print(
"===",
"=" * 10
+ " "
+ "=" * max_file
@@ -1444,21 +1462,60 @@ class Summary:
+ " "
+ "=" * 7
+ " "
+ "=" * max_title
+ "=" * max_title,
)
print(
"\n".join(
[
(color2 if n % 2 == 0 else color1)
+ f"{x['date']} {x['file']:{max_file}s} "
(color2 if n % 2 == 0 else color1) + f"{n:3d} "
f"{x['date']} {x['file']:{max_file}s} "
f"{x['metric']:8.5f} "
f"{x['duration']/3600:7.3f} "
f"{x['title']}"
for n, x in enumerate(data)
for n, x in enumerate(self.data_filtered)
]
)
)
def manage_results(self, excel, is_test):
"""Manage results showed in the summary
return True if excel file is created False otherwise
"""
num = ""
book = None
while True:
print(
"Which result do you want to report? (q to quit, r to list "
"again, number to report): ",
end="",
)
num = get_input(is_test)
if num == "r":
self.list_results()
if num == "q":
if excel:
if book is not None:
book.close()
return True
return False
if num.isdigit() and int(num) < len(self.data) and int(num) >= 0:
rep = Report(self.data_filtered[int(num)]["file"], self.hidden)
rep.report()
if excel and not self.hidden:
if book is None:
file_name = Files.be_list_excel
book = xlsxwriter.Workbook(
file_name, {"nan_inf_to_errors": True}
)
excel = Excel(
file_name=self.data_filtered[int(num)]["file"],
book=book,
)
excel.report()
else:
if num not in ("r", "q"):
print(f"Invalid option {num}. Try again!")
def show_result(self, data: dict, title: str = "") -> None:
def whites(n: int) -> str:
return " " * n + color1 + "*"

1
benchmark/Utils.py
View File

@@ -28,6 +28,7 @@ class Files:
benchmark_r = "benchmark.r"
dot_env = ".env"
datasets_report_excel = "ReportDatasets.xlsx"
be_list_excel = "some_results.xlsx"
@staticmethod
def exreport_output(score):

2
benchmark/_version.py
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@@ -1 +1 @@
__version__ = "0.3.0"
__version__ = "0.4.0"

60
benchmark/scripts/be_list.py
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@@ -1,7 +1,7 @@
#! /usr/bin/env python
import os
from benchmark.Results import Summary
from benchmark.Utils import Folders
from benchmark.Utils import Folders, Files
from benchmark.Arguments import Arguments
"""List experiments of a model
@@ -12,6 +12,7 @@ def main(args_test=None):
arguments = Arguments()
arguments.xset("number").xset("model", required=False).xset("key")
arguments.xset("hidden").xset("nan").xset("score", required=False)
arguments.xset("excel")
args = arguments.parse(args_test)
data = Summary(hidden=args.hidden)
data.acquire()
@@ -22,32 +23,39 @@ def main(args_test=None):
sort_key=args.key,
number=args.number,
)
is_test = args_test is not None
if not args.nan:
excel_generated = data.manage_results(args.excel, is_test)
if args.excel and excel_generated:
print(f"Generated file: {Files.be_list_excel}")
Files.open(Files.be_list_excel, is_test)
except ValueError as e:
print(e)
else:
if args.nan:
results_nan = []
results = data.get_results_criteria(
score=args.score,
model=args.model,
input_data=None,
sort_key=args.key,
number=args.number,
return
if args.nan:
results_nan = []
results = data.get_results_criteria(
score=args.score,
model=args.model,
input_data=None,
sort_key=args.key,
number=args.number,
)
for result in results:
if result["metric"] != result["metric"]:
results_nan.append(result)
if results_nan != []:
print(
"\n"
+ "*" * 30
+ " Results with nan moved to hidden "
+ "*" * 30
)
for result in results:
if result["metric"] != result["metric"]:
results_nan.append(result)
if results_nan != []:
print(
"\n"
+ "*" * 30
+ " Results with nan moved to hidden "
+ "*" * 30
data.data_filtered = []
data.list_results(input_data=results_nan)
for result in results_nan:
name = result["file"]
os.rename(
os.path.join(Folders.results, name),
os.path.join(Folders.hidden_results, name),
)
data.list_results(input_data=results_nan)
for result in results_nan:
name = result["file"]
os.rename(
os.path.join(Folders.results, name),
os.path.join(Folders.hidden_results, name),
)

1
benchmark/tests/.gitignore vendored
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@@ -1 +1,2 @@
ReportDatasets.xlsx
some_results.xlsx

5
benchmark/tests/Report_test.py
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@@ -2,11 +2,14 @@ import os
from io import StringIO
from unittest.mock import patch
from .TestBase import TestBase
from ..Results import Report, BaseReport, ReportBest, ReportDatasets
from ..Results import Report, BaseReport, ReportBest, ReportDatasets, get_input
from ..Utils import Symbols
class ReportTest(TestBase):
def test_get_input(self):
self.assertEqual(get_input(is_test=True), "test")
def test_BaseReport(self):
with patch.multiple(BaseReport, __abstractmethods__=set()):
file_name = os.path.join(

4
benchmark/tests/scripts/Be_Grid_test.py
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@@ -4,6 +4,10 @@ from ...Utils import Folders, Files
from ..TestBase import TestBase
def get_test():
return "hola"
class BeGridTest(TestBase):
def setUp(self):
self.prepare_scripts_env()

65
benchmark/tests/scripts/Be_List_test.py
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@@ -1,5 +1,7 @@
import os
from ...Utils import Folders, NO_RESULTS
from unittest.mock import patch
from openpyxl import load_workbook
from ...Utils import Folders, Files, NO_RESULTS
from ..TestBase import TestBase
@@ -7,12 +9,64 @@ class BeListTest(TestBase):
def setUp(self):
self.prepare_scripts_env()
def test_be_list(self):
@patch("benchmark.Results.get_input", return_value="q")
def test_be_list(self, input_data):
stdout, stderr = self.execute_script("be_list", ["-m", "STree"])
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "summary_list_model")
self.check_output_file(stdout, "be_list_model")
def test_be_list_no_data(self):
@patch("benchmark.Results.get_input", side_effect=iter(["x", "q"]))
def test_be_list_invalid_option(self, input_data):
stdout, stderr = self.execute_script("be_list", ["-m", "STree"])
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_model_invalid")
@patch("benchmark.Results.get_input", side_effect=iter(["0", "q"]))
def test_be_list_report(self, input_data):
stdout, stderr = self.execute_script("be_list", ["-m", "STree"])
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_report")
@patch("benchmark.Results.get_input", side_effect=iter(["q"]))
def test_be_list_report_excel_none(self, input_data):
stdout, stderr = self.execute_script(
"be_list", ["-m", "STree", "-x", "1"]
)
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_model")
@patch("benchmark.Results.get_input", side_effect=iter(["r", "q"]))
def test_be_list_twice(self, input_data):
stdout, stderr = self.execute_script("be_list", ["-m", "STree"])
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_model_2")
@patch("benchmark.Results.get_input", side_effect=iter(["2", "q"]))
def test_be_list_report_excel(self, input_data):
stdout, stderr = self.execute_script(
"be_list", ["-m", "STree", "-x", "1"]
)
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_report_excel")
book = load_workbook(Files.be_list_excel)
sheet = book["STree"]
self.check_excel_sheet(sheet, "excel")
@patch("benchmark.Results.get_input", side_effect=iter(["2", "1", "q"]))
def test_be_list_report_excel_twice(self, input_data):
stdout, stderr = self.execute_script(
"be_list", ["-m", "STree", "-x", "1"]
)
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_report_excel_2")
book = load_workbook(Files.be_list_excel)
sheet = book["STree"]
self.check_excel_sheet(sheet, "excel")
sheet = book["STree2"]
self.check_excel_sheet(sheet, "excel2")
@patch("benchmark.Results.get_input", return_value="q")
def test_be_list_no_data(self, input_data):
stdout, stderr = self.execute_script(
"be_list", ["-m", "Wodt", "-s", "f1-macro"]
)
@@ -41,7 +95,8 @@ class BeListTest(TestBase):
swap_files(Folders.results, Folders.hidden_results, file_name)
self.fail("test_be_list_nan() should not raise exception")
def test_be_list_nan_no_nan(self):
@patch("benchmark.Results.get_input", return_value="q")
def test_be_list_nan_no_nan(self, input_data):
stdout, stderr = self.execute_script("be_list", ["--nan", "1"])
self.assertEqual(stderr.getvalue(), "")
self.check_output_file(stdout, "be_list_no_nan")

6
benchmark/tests/test_files/be_list_model.test Normal file
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@@ -0,0 +1,6 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report):

11
benchmark/tests/test_files/be_list_model_2.test Normal file
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@@ -0,0 +1,11 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report):  # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report):

7
benchmark/tests/test_files/be_list_model_invalid.test Normal file
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@@ -0,0 +1,7 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report): Invalid option x. Try again!
Which result do you want to report? (q to quit, r to list again, number to report):

22
benchmark/tests/test_files/be_list_nan.test
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@@ -1,13 +1,13 @@
Date File Score Time(h) Title
========== ================================================================ ======== ======= ============================================
2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 # Date File Score Time(h) Title
=== ========== ================================================================ ======== ======= ============================================
 0 2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 5 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
****************************** Results with nan moved to hidden ******************************
Date File Score Time(h) Title
========== ================================================================ ======== ======= =======================
2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters
 # Date File Score Time(h) Title
=== ========== ================================================================ ======== ======= =======================
 0 2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters

14
benchmark/tests/test_files/be_list_no_nan.test
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@@ -1,7 +1,7 @@
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 1 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 2 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 3 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 4 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters

21
benchmark/tests/test_files/be_list_report.test Normal file
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@@ -0,0 +1,21 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report): *************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-11-01 19:17:07 *
* default B *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 4115.04 seconds, 1.14 hours, on macbook-pro *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 18.78 9.88 5.90 0.970000±0.0020 0.233304±0.0481 {'max_features': 'auto', 'splitter': 'mutual'}
balloons 16 4 2 4.72 2.86 2.78 0.556667±0.2941 0.021352±0.0058 {'max_features': 'auto', 'splitter': 'mutual'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0379 *
*************************************************************************************************************************
Which result do you want to report? (q to quit, r to list again, number to report):

21
benchmark/tests/test_files/be_list_report_excel.test Normal file
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@@ -0,0 +1,21 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report): *************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
*************************************************************************************************************************
Which result do you want to report? (q to quit, r to list again, number to report): Generated file: some_results.xlsx

36
benchmark/tests/test_files/be_list_report_excel_2.test Normal file
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@@ -0,0 +1,36 @@
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
Which result do you want to report? (q to quit, r to list again, number to report): *************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
*************************************************************************************************************************
Which result do you want to report? (q to quit, r to list again, number to report): *************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-10-27 09:40:40 *
* default A *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 3395.01 seconds, 0.94 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 11.08 5.90 5.90 0.980000±0.0010 0.285207±0.0603 {'splitter': 'best', 'max_features': 'auto'}
balloons 16 4 2 4.12 2.56 2.56 0.695000±0.2757 0.021201±0.0035 {'splitter': 'best', 'max_features': 'auto'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0416 *
*************************************************************************************************************************
Which result do you want to report? (q to quit, r to list again, number to report): Generated file: some_results.xlsx

28
benchmark/tests/test_files/be_main_best.test
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@@ -1,16 +1,16 @@
************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-09 00:15:25 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.80 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-09 00:15:25 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.80 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balance-scale 625 4 3 23.32 12.16 6.44 0.840160±0.0304 0.013745±0.0019 {'splitter': 'best', 'max_features': 'auto'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000388±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0422 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 23.32 12.16 6.44 0.840160±0.0304 0.013745±0.0019 {'splitter': 'best', 'max_features': 'auto'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000388±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0422 *
*************************************************************************************************************************
Results in results/results_accuracy_STree_iMac27_2022-05-09_00:15:25_0.json

28
benchmark/tests/test_files/be_main_complete.test
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@@ -1,16 +1,16 @@
************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-08 20:14:43 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.48 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-08 20:14:43 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.48 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balance-scale 625 4 3 17.36 9.18 6.18 0.908480±0.0247 0.007388±0.0013 {}
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000664±0.0002 {}
************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0390 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 17.36 9.18 6.18 0.908480±0.0247 0.007388±0.0013 {}
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000664±0.0002 {}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0390 *
*************************************************************************************************************************
Results in results/results_accuracy_STree_iMac27_2022-05-08_20:14:43_0.json

26
benchmark/tests/test_files/be_main_dataset.test
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@@ -1,15 +1,15 @@
************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-08 19:38:28 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.06 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-08 19:38:28 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.06 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000671±0.0001 {}
************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0165 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000671±0.0001 {}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0165 *
*************************************************************************************************************************
Partial result file removed: results/results_accuracy_STree_iMac27_2022-05-08_19:38:28_0.json

28
benchmark/tests/test_files/be_main_grid.test
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@@ -1,16 +1,16 @@
************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-09 00:21:06 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.89 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.4 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2022-05-09 00:21:06 *
* test *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 0.89 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balance-scale 625 4 3 26.12 13.56 7.94 0.910720±0.0249 0.015852±0.0027 {'C': 1.0, 'kernel': 'liblinear', 'multiclass_strategy': 'ovr'}
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000640±0.0001 {'C': 1.0, 'kernel': 'linear', 'multiclass_strategy': 'ovr'}
************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0391 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 26.12 13.56 7.94 0.910720±0.0249 0.015852±0.0027 {'C': 1.0, 'kernel': 'liblinear', 'multiclass_strategy': 'ovr'}
balloons 16 4 2 4.64 2.82 2.66 0.663333±0.3009 0.000640±0.0001 {'C': 1.0, 'kernel': 'linear', 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0391 *
*************************************************************************************************************************
Results in results/results_accuracy_STree_iMac27_2022-05-09_00:21:06_0.json

14
benchmark/tests/test_files/be_summary_list_model.test
View File

@@ -26,10 +26,10 @@
* results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json *
* *
*********************************************************************************
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest

14
benchmark/tests/test_files/be_summary_list_score.test
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@@ -26,10 +26,10 @@
* results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json *
* *
*********************************************************************************
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest

14
benchmark/tests/test_files/be_summary_list_score_all.test
View File

@@ -26,13 +26,13 @@
* results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json *
* *
*********************************************************************************
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
** No results found **
** No results found **
** No results found **

14
benchmark/tests/test_files/be_summary_list_score_model.test
View File

@@ -26,10 +26,10 @@
* results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json *
* *
*********************************************************************************
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest

48
benchmark/tests/test_files/excel2.test Normal file
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@@ -0,0 +1,48 @@
1;1;" STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-10-27 09:40:40"
2;1;" default A"
3;1;" Score is accuracy"
3;2;" Execution time"
3;5;"3,395.01 s"
3;7;" "
3;8;"Platform"
3;9;"iMac27"
3;10;"Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]"
4;5;" 0.94 h"
4;10;"Stratified: False"
6;1;"Dataset"
6;2;"Samples"
6;3;"Features"
6;4;"Classes"
6;5;"Nodes"
6;6;"Leaves"
6;7;"Depth"
6;8;"Score"
6;9;"Score Std."
6;10;"Time"
6;11;"Time Std."
6;12;"Hyperparameters"
7;1;"balance-scale"
7;2;"625"
7;3;"4"
7;4;"3"
7;5;"11.08"
7;6;"5.9"
7;7;"5.9"
7;8;"0.98"
7;9;"0.001"
7;10;"0.2852065515518188"
7;11;"0.06031593282605064"
7;12;"{'splitter': 'best', 'max_features': 'auto'}"
8;1;"balloons"
8;2;"16"
8;3;"4"
8;4;"2"
8;5;"4.12"
8;6;"2.56"
8;7;"2.56"
8;8;"0.695"
8;9;"0.2756860130252853"
8;10;"0.02120100021362305"
8;11;"0.003526023309468471"
8;12;"{'splitter': 'best', 'max_features': 'auto'}"
10;1;"** accuracy compared to STree_default (liblinear-ovr) .: 0.0416"

28
benchmark/tests/test_files/report.test
View File

@@ -1,15 +1,15 @@
************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
*************************************************************************************************************************

30
benchmark/tests/test_files/report_compared.test
View File

@@ -1,16 +1,16 @@
************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
************************************************************************************************************************
*************************************************************************************************************************
* STree ver. 1.2.3 Python ver. 3.11x with 5 Folds cross validation and 10 random seeds. 2021-09-30 11:42:07 *
* With gridsearched hyperparameters *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================ ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850✔ 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
************************************************************************************************************************
* ✔ Equal to best .....: 1 *
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
************************************************************************************************************************
Dataset Sampl. Feat. Cls Nodes Leaves Depth Score Time Hyperparameters
============================== ====== ===== === ======= ======= ======= =============== ================= ===============
balance-scale 625 4 3 7.00 4.00 3.00 0.970560±0.0150 0.014049±0.0020 {'C': 10000.0, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
balloons 16 4 2 3.00 2.00 2.00 0.860000±0.2850✔ 0.000854±0.0000 {'C': 7, 'gamma': 0.1, 'kernel': 'rbf', 'max_iter': 10000.0, 'multiclass_strategy': 'ovr'}
*************************************************************************************************************************
* ✔ Equal to best .....: 1 *
* accuracy compared to STree_default (liblinear-ovr) .: 0.0454 *
*************************************************************************************************************************

8
benchmark/tests/test_files/summary_list_hidden.test
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@@ -1,4 +1,4 @@
Date File Score Time(h) Title
========== ================================================================ ======== ======= =======================
2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters
2021-11-01 results_accuracy_STree_iMac27_2021-11-01_23:55:16_0.json 0.97446 0.098 default
 # Date File Score Time(h) Title
=== ========== ================================================================ ======== ======= =======================
 0 2022-05-04 results_accuracy_XGBoost_MacBookpro16_2022-05-04_11:00:35_0.json nan 3.091 Default hyperparameters
 1 2021-11-01 results_accuracy_STree_iMac27_2021-11-01_23:55:16_0.json 0.97446 0.098 default

10
benchmark/tests/test_files/summary_list_model.test
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@@ -1,5 +1,5 @@
Date File Score Time(h) Title
========== ============================================================= ======== ======= =================================
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 # Date File Score Time(h) Title
=== ========== ============================================================= ======== ======= =================================
 0 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 1 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 2 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters

10
benchmark/tests/test_files/summary_list_n.test
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Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 1 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 2 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B

14
benchmark/tests/test_files/summary_list_score.test
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@@ -1,7 +1,7 @@
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 1 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 2 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 3 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 4 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters

14
benchmark/tests/test_files/summary_show_top.test
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@@ -1,7 +1,7 @@
Date File Score Time(h) Title
========== =============================================================== ======== ======= ============================================
2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest
 # Date File Score Time(h) Title
=== ========== =============================================================== ======== ======= ============================================
 0 2021-09-30 results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json 0.04544 0.173 With gridsearched hyperparameters
 1 2022-04-20 results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json 0.04341 6.275 Gridsearched hyperparams v022.1b random_init
 2 2021-10-27 results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json 0.04158 0.943 default A
 3 2021-11-01 results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json 0.03790 1.143 default B
 4 2022-01-14 results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json 0.03627 0.076 Test default paramters with RandomForest