Doctorado-ML/benchmark
1
0
Fork 0
mirror of https://github.com/Doctorado-ML/benchmark.git synced 2025-08-16 16:05:54 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add new models and repair tests

Browse Source
This commit is contained in:
Ricardo Montañana Gómez
2023-02-21 17:08:50 +01:00
parent 27bf414db9
commit e2504c7ae9
21 changed files with 29 additions and 279 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
benchmark/Datasets.py
View File

@@ -229,7 +229,7 @@ class Datasets:
-------
tuple (X, y) of numpy.ndarray
"""
discretiz = FImdlp(algorithm=0)
discretiz = FImdlp()
return discretiz.fit_transform(X, y)
def __iter__(self) -> Diterator:

2
benchmark/Experiments.py
View File

@@ -240,7 +240,7 @@ class Experiment:
cv=kfold,
fit_params=fit_params,
return_estimator=True,
scoring=self.score_name,
scoring=self.score_name.replace("-", "_"),
)
if np.isnan(res["test_score"]).any():
if not self.ignore_nan:

2
benchmark/Models.py
View File

@@ -8,7 +8,7 @@ from sklearn.ensemble import (
)
from sklearn.svm import SVC
from stree import Stree
from bayesclass.clfs import TAN, KDB, AODE, KDBNew, TANNew
from bayesclass.clfs import TAN, KDB, AODE, KDBNew, TANNew, AODENew
from wodt import Wodt
from odte import Odte
from xgboost import XGBClassifier

3
benchmark/tests/.env
View File

@@ -9,4 +9,5 @@ seeds=[57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
discretize=0
nodes=Nodes
leaves=Leaves
depth=Depth
depth=Depth
fit_features=0

3
benchmark/tests/.env.arff
View File

@@ -8,4 +8,5 @@ seeds=[271, 314, 171]
discretize=1
nodes=Nodes
leaves=Leaves
depth=Depth
depth=Depth
fit_features=1

3
benchmark/tests/.env.dist
View File

@@ -9,4 +9,5 @@ seeds=[57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
discretize=0
nodes=Nodes
leaves=Leaves
depth=Depth
depth=Depth
fit_features=0

3
benchmark/tests/.env.surcov
View File

@@ -9,4 +9,5 @@ seeds=[57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
discretize=0
nodes=Nodes
leaves=Leaves
depth=Depth
depth=Depth
fit_features=0

7
benchmark/tests/Experiment_test.py
View File

@@ -143,9 +143,9 @@ class ExperimentTest(TestBase):
expected = {
"state_names": {
"sepallength": [0, 1, 2],
"sepalwidth": [0, 1, 3, 4],
"sepalwidth": [0, 1, 2, 3, 4, 5],
"petallength": [0, 1, 2, 3],
"petalwidth": [0, 1, 2, 3],
"petalwidth": [0, 1, 2],
},
"features": [
"sepallength",
@@ -161,6 +161,9 @@ class ExperimentTest(TestBase):
self.assertEqual(computed["state_names"][key], value)
for feature in expected["features"]:
self.assertIn(feature, computed["features"])
# Ask for states of a dataset that does not exist
computed = exp._build_fit_params("not_existing")
self.assertTrue("states" not in computed)
@patch("sys.stdout", new_callable=StringIO)
def test_experiment_with_nan_not_ignored(self, mock_output):

1
benchmark/tests/Util_test.py
View File

@@ -183,6 +183,7 @@ class UtilTest(TestBase):
"nodes": "Nodes",
"leaves": "Leaves",
"depth": "Depth",
"fit_features": "0",
}
computed = EnvData().load()
self.assertDictEqual(computed, expected)

60
benchmark/tests/results/results_accuracy_ODTE_Galgo_2022-04-20_10:52:20_0.json
View File

@@ -1,59 +1 @@
{
"score_name": "accuracy",
"title": "Gridsearched hyperparams v022.1b random_init",
"model": "ODTE",
"version": "0.3.2",
"language_version": "3.11x",
"language": "Python",
"stratified": false,
"folds": 5,
"date": "2022-04-20",
"time": "10:52:20",
"duration": 22591.471411943436,
"seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1],
"platform": "Galgo",
"results": [
{
"dataset": "balance-scale",
"samples": 625,
"features": 4,
"classes": 3,
"hyperparameters": {
"base_estimator__C": 57,
"base_estimator__gamma": 0.1,
"base_estimator__kernel": "rbf",
"base_estimator__multiclass_strategy": "ovr",
"n_estimators": 100,
"n_jobs": -1
},
"nodes": 7.361199999999999,
"leaves": 4.180599999999999,
"depth": 3.536,
"score": 0.96352,
"score_std": 0.024949741481626608,
"time": 0.31663217544555666,
"time_std": 0.19918813895255585
},
{
"dataset": "balloons",
"samples": 16,
"features": 4,
"classes": 2,
"hyperparameters": {
"base_estimator__C": 5,
"base_estimator__gamma": 0.14,
"base_estimator__kernel": "rbf",
"base_estimator__multiclass_strategy": "ovr",
"n_estimators": 100,
"n_jobs": -1
},
"nodes": 2.9951999999999996,
"leaves": 1.9975999999999998,
"depth": 1.9975999999999998,
"score": 0.785,
"score_std": 0.2461311755051675,
"time": 0.11560620784759522,
"time_std": 0.012784241828599895
}
]
}
{"score_name": "accuracy", "title": "Gridsearched hyperparams v022.1b random_init", "model": "ODTE", "version": "0.3.2", "language_version": "3.11x", "language": "Python", "stratified": false, "folds": 5, "date": "2022-04-20", "time": "10:52:20", "duration": 22591.471411943436, "seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1], "platform": "Galgo", "results": [{"dataset": "balance-scale", "samples": 625, "features": 4, "classes": 3, "hyperparameters": {"base_estimator__C": 57, "base_estimator__gamma": 0.1, "base_estimator__kernel": "rbf", "base_estimator__multiclass_strategy": "ovr", "n_estimators": 100, "n_jobs": -1}, "nodes": 7.361199999999999, "leaves": 4.180599999999999, "depth": 3.536, "score": 0.96352, "score_std": 0.024949741481626608, "time": 0.31663217544555666, "time_std": 0.19918813895255585}, {"dataset": "balloons", "samples": 16, "features": 4, "classes": 2, "hyperparameters": {"base_estimator__C": 5, "base_estimator__gamma": 0.14, "base_estimator__kernel": "rbf", "base_estimator__multiclass_strategy": "ovr", "n_estimators": 100, "n_jobs": -1}, "nodes": 2.9951999999999996, "leaves": 1.9975999999999998, "depth": 1.9975999999999998, "score": 0.785, "score_std": 0.2461311755051675, "time": 0.11560620784759522, "time_std": 0.012784241828599895}], "discretized": false}

46
benchmark/tests/results/results_accuracy_RandomForest_iMac27_2022-01-14_12:39:30_0.json
View File

@@ -1,45 +1 @@
{
"score_name": "accuracy",
"title": "Test default paramters with RandomForest",
"model": "RandomForest",
"version": "-",
"language_version": "3.11x",
"language": "Python",
"stratified": false,
"folds": 5,
"date": "2022-01-14",
"time": "12:39:30",
"duration": 272.7363500595093,
"seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1],
"platform": "iMac27",
"results": [
{
"dataset": "balance-scale",
"samples": 625,
"features": 4,
"classes": 3,
"hyperparameters": {},
"nodes": 196.91440000000003,
"leaves": 98.42,
"depth": 10.681399999999998,
"score": 0.83616,
"score_std": 0.02649630917694009,
"time": 0.08222018241882324,
"time_std": 0.0013026326815120633
},
{
"dataset": "balloons",
"samples": 16,
"features": 4,
"classes": 2,
"hyperparameters": {},
"nodes": 9.110800000000001,
"leaves": 4.58,
"depth": 3.0982,
"score": 0.625,
"score_std": 0.24958298553119898,
"time": 0.07016648769378662,
"time_std": 0.002460508923990468
}
]
}
{"score_name": "accuracy", "title": "Test default paramters with RandomForest", "model": "RandomForest", "version": "-", "language_version": "3.11x", "language": "Python", "stratified": false, "folds": 5, "date": "2022-01-14", "time": "12:39:30", "duration": 272.7363500595093, "seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1], "platform": "iMac27", "results": [{"dataset": "balance-scale", "samples": 625, "features": 4, "classes": 3, "hyperparameters": {}, "nodes": 196.91440000000003, "leaves": 98.42, "depth": 10.681399999999998, "score": 0.83616, "score_std": 0.02649630917694009, "time": 0.08222018241882324, "time_std": 0.0013026326815120633}, {"dataset": "balloons", "samples": 16, "features": 4, "classes": 2, "hyperparameters": {}, "nodes": 9.110800000000001, "leaves": 4.58, "depth": 3.0982, "score": 0.625, "score_std": 0.24958298553119898, "time": 0.07016648769378662, "time_std": 0.002460508923990468}], "discretized": false}

58
benchmark/tests/results/results_accuracy_STree_iMac27_2021-09-30_11:42:07_0.json
View File

@@ -1,57 +1 @@
{
"score_name": "accuracy",
"model": "STree",
"stratified": false,
"folds": 5,
"language_version": "3.11x",
"language": "Python",
"date": "2021-09-30",
"time": "11:42:07",
"duration": 624.2505249977112,
"seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1],
"platform": "iMac27",
"results": [
{
"dataset": "balance-scale",
"samples": 625,
"features": 4,
"classes": 3,
"hyperparameters": {
"C": 10000,
"gamma": 0.1,
"kernel": "rbf",
"max_iter": 10000,
"multiclass_strategy": "ovr"
},
"nodes": 7.0,
"leaves": 4.0,
"depth": 3.0,
"score": 0.97056,
"score_std": 0.015046806970251203,
"time": 0.01404867172241211,
"time_std": 0.002026269126958884
},
{
"dataset": "balloons",
"samples": 16,
"features": 4,
"classes": 2,
"hyperparameters": {
"C": 7,
"gamma": 0.1,
"kernel": "rbf",
"max_iter": 10000,
"multiclass_strategy": "ovr"
},
"nodes": 3.0,
"leaves": 2.0,
"depth": 2.0,
"score": 0.86,
"score_std": 0.28501461950807594,
"time": 0.0008541679382324218,
"time_std": 3.629469326417878e-5
}
],
"title": "With gridsearched hyperparameters",
"version": "1.2.3"
}
{"score_name": "accuracy", "model": "STree", "stratified": false, "folds": 5, "language_version": "3.11x", "language": "Python", "date": "2021-09-30", "time": "11:42:07", "duration": 624.2505249977112, "seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1], "platform": "iMac27", "results": [{"dataset": "balance-scale", "samples": 625, "features": 4, "classes": 3, "hyperparameters": {"C": 10000, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000, "multiclass_strategy": "ovr"}, "nodes": 7.0, "leaves": 4.0, "depth": 3.0, "score": 0.97056, "score_std": 0.015046806970251203, "time": 0.01404867172241211, "time_std": 0.002026269126958884}, {"dataset": "balloons", "samples": 16, "features": 4, "classes": 2, "hyperparameters": {"C": 7, "gamma": 0.1, "kernel": "rbf", "max_iter": 10000, "multiclass_strategy": "ovr"}, "nodes": 3.0, "leaves": 2.0, "depth": 2.0, "score": 0.86, "score_std": 0.28501461950807594, "time": 0.0008541679382324218, "time_std": 3.629469326417878e-05}], "title": "With gridsearched hyperparameters", "version": "1.2.3", "discretized": false}

52
benchmark/tests/results/results_accuracy_STree_iMac27_2021-10-27_09:40:40_0.json
View File

@@ -1,51 +1 @@
{
"score_name": "accuracy",
"model": "STree",
"language": "Python",
"language_version": "3.11x",
"stratified": false,
"folds": 5,
"date": "2021-10-27",
"time": "09:40:40",
"duration": 3395.009148836136,
"seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1],
"platform": "iMac27",
"results": [
{
"dataset": "balance-scale",
"samples": 625,
"features": 4,
"classes": 3,
"hyperparameters": {
"splitter": "best",
"max_features": "auto"
},
"nodes": 11.08,
"leaves": 5.9,
"depth": 5.9,
"score": 0.98,
"score_std": 0.001,
"time": 0.28520655155181884,
"time_std": 0.06031593282605064
},
{
"dataset": "balloons",
"samples": 16,
"features": 4,
"classes": 2,
"hyperparameters": {
"splitter": "best",
"max_features": "auto"
},
"nodes": 4.12,
"leaves": 2.56,
"depth": 2.56,
"score": 0.695,
"score_std": 0.2756860130252853,
"time": 0.021201000213623047,
"time_std": 0.003526023309468471
}
],
"title": "default A",
"version": "1.2.3"
}
{"score_name": "accuracy", "model": "STree", "language": "Python", "language_version": "3.11x", "stratified": false, "folds": 5, "date": "2021-10-27", "time": "09:40:40", "duration": 3395.009148836136, "seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1], "platform": "iMac27", "results": [{"dataset": "balance-scale", "samples": 625, "features": 4, "classes": 3, "hyperparameters": {"splitter": "best", "max_features": "auto"}, "nodes": 11.08, "leaves": 5.9, "depth": 5.9, "score": 0.98, "score_std": 0.001, "time": 0.28520655155181884, "time_std": 0.06031593282605064}, {"dataset": "balloons", "samples": 16, "features": 4, "classes": 2, "hyperparameters": {"splitter": "best", "max_features": "auto"}, "nodes": 4.12, "leaves": 2.56, "depth": 2.56, "score": 0.695, "score_std": 0.2756860130252853, "time": 0.021201000213623047, "time_std": 0.003526023309468471}], "title": "default A", "version": "1.2.3", "discretized": false}

52
benchmark/tests/results/results_accuracy_STree_macbook-pro_2021-11-01_19:17:07_0.json
View File

@@ -1,51 +1 @@
{
"score_name": "accuracy",
"model": "STree",
"language_version": "3.11x",
"language": "Python",
"stratified": false,
"folds": 5,
"date": "2021-11-01",
"time": "19:17:07",
"duration": 4115.042420864105,
"seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1],
"platform": "macbook-pro",
"results": [
{
"dataset": "balance-scale",
"samples": 625,
"features": 4,
"classes": 3,
"hyperparameters": {
"max_features": "auto",
"splitter": "mutual"
},
"nodes": 18.78,
"leaves": 9.88,
"depth": 5.9,
"score": 0.97,
"score_std": 0.002,
"time": 0.23330417156219482,
"time_std": 0.048087665954193885
},
{
"dataset": "balloons",
"samples": 16,
"features": 4,
"classes": 2,
"hyperparameters": {
"max_features": "auto",
"splitter": "mutual"
},
"nodes": 4.72,
"leaves": 2.86,
"depth": 2.78,
"score": 0.5566666666666668,
"score_std": 0.2941277122460771,
"time": 0.021352062225341795,
"time_std": 0.005808742398555902
}
],
"title": "default B",
"version": "1.2.3"
}
{"score_name": "accuracy", "model": "STree", "language_version": "3.11x", "language": "Python", "stratified": false, "folds": 5, "date": "2021-11-01", "time": "19:17:07", "duration": 4115.042420864105, "seeds": [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1], "platform": "macbook-pro", "results": [{"dataset": "balance-scale", "samples": 625, "features": 4, "classes": 3, "hyperparameters": {"max_features": "auto", "splitter": "mutual"}, "nodes": 18.78, "leaves": 9.88, "depth": 5.9, "score": 0.97, "score_std": 0.002, "time": 0.23330417156219482, "time_std": 0.048087665954193885}, {"dataset": "balloons", "samples": 16, "features": 4, "classes": 2, "hyperparameters": {"max_features": "auto", "splitter": "mutual"}, "nodes": 4.72, "leaves": 2.86, "depth": 2.78, "score": 0.5566666666666668, "score_std": 0.2941277122460771, "time": 0.021352062225341795, "time_std": 0.005808742398555902}], "title": "default B", "version": "1.2.3", "discretized": false}

2
benchmark/tests/test_files/be_list_report.test
View File

@@ -6,7 +6,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 4115.04 seconds, 1.14 hours, on macbook-pro *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/be_main_best.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 0.80 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/be_main_complete.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 0.48 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/be_main_dataset.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 with only one dataset *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 0.06 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/be_main_grid.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 0.89 seconds, 0.00 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/report.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************

2
benchmark/tests/test_files/report_compared.test
View File

@@ -1,7 +1,7 @@
*************************************************************************************************************************
* 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 *
* Random seeds: [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1] Stratified: False Discretized: False *
* Execution took 624.25 seconds, 0.17 hours, on iMac27 *
* Score is accuracy *
*************************************************************************************************************************