65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
import json
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import os
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from locale import atof
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import pandas as pd
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import numpy as np
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lines = open("results_pbc4.txt").readlines()
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results = []
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for line in lines:
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(
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dataset,
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accuracy,
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accuracy_std,
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time_spent,
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time_std,
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nodes,
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nodes_std,
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) = line.split(";")
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data = pd.read_csv(
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os.path.join("data.r", f"{dataset}_R.dat"),
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sep="\t",
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index_col=0,
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)
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X = data.drop("clase", axis=1).to_numpy()
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y = data["clase"].to_numpy()
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samples, features = X.shape
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n_classes = len(np.unique(y))
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record = {}
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record["dataset"] = dataset
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record["samples"] = samples
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record["features"] = features
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record["classes"] = n_classes
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record["hyperparameters"] = {}
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record["nodes"] = atof(nodes)
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record["leaves"] = 0.0
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record["depth"] = 0.0
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record["score"] = atof(accuracy)
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record["score_std"] = atof(accuracy_std)
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record["time"] = atof(time_spent)
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record["time_std"] = atof(time_std)
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results.append(record)
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output = {}
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output["score_name"] = "accuracy"
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output["title"] = "PBC4cip Ensemble execution"
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output["model"] = "pbc4cip"
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output["version"] = "1.0"
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output["stratified"] = True
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output["folds"] = 5
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output["date"] = "2024-12-23"
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output["time"] = "17:10:00"
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output["duration"] = 1.25 * 3600
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output["seeds"] = [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]
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output["platform"] = "HugeFedora"
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output["language"] = "java"
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output["language_version"] = "openjdk 17.0.1"
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output["discretization_algorithm"] = "mdlp"
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output["smooth_strategy"] = "ORIGINAL"
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output["discretized"] = False
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output["results"] = results
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file_name = "results_accuracy_pbc4cip_HugeFedora_2024-12-23_17:10:00_1.json"
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with open(file_name, "w") as f:
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json.dump(output, f)
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print(f"File {file_name} created.")
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