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# Author: Simon Blanke |
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# Email: [email protected] |
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# License: MIT License |
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import pandas as pd |
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from sklearn.datasets import load_iris |
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from sklearn.tree import DecisionTreeClassifier |
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from sklearn.model_selection import cross_val_score |
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data = load_iris() |
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X_np = data.data |
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y_np = data.target |
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iris_X_train_columns = ["x1", "x2", "x3", "x4"] |
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X_pd = pd.DataFrame(X_np, columns=iris_X_train_columns) |
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y_pd = pd.DataFrame(y_np, columns=["y1"]) |
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View Code Duplication |
def model(para, X_train, y_train): |
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model = DecisionTreeClassifier( |
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criterion=para["criterion"], |
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max_depth=para["max_depth"], |
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min_samples_split=para["min_samples_split"], |
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min_samples_leaf=para["min_samples_leaf"], |
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) |
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scores = cross_val_score(model, X_train, y_train, cv=3) |
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return scores.mean() |
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search_config = { |
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model: { |
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"criterion": ["gini", "entropy"], |
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"max_depth": range(1, 21), |
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"min_samples_split": range(2, 21), |
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"min_samples_leaf": range(1, 21), |
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} |
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} |
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""" |
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def test_data(): |
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from hyperactive import Hyperactive |
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opt0 = Hyperactive(search_config) |
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opt0.search(X_np, y_np) |
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opt1 = Hyperactive(search_config) |
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opt1.search(X_pd, y_pd) |
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""" |
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SimonBlanke /
Hyperactive
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