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from sklearn.datasets import load_breast_cancer |
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from sklearn.model_selection import cross_val_score |
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from mlxtend.classifier import EnsembleVoteClassifier |
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from sklearn.ensemble import GradientBoostingClassifier |
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from sklearn.neural_network import MLPClassifier |
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from sklearn.svm import SVC |
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from hyperactive import Hyperactive |
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data = load_breast_cancer() |
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X, y = data.data, data.target |
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def model(para, X, y): |
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gbc = GradientBoostingClassifier( |
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n_estimators=para["n_estimators"], max_depth=para["max_depth"] |
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) |
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mlp = MLPClassifier(hidden_layer_sizes=para["hidden_layer_sizes"]) |
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svc = SVC(gamma="auto", probability=True) |
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eclf = EnsembleVoteClassifier( |
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clfs=[gbc, mlp, svc], weights=[2, 1, 1], voting="soft" |
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) |
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scores = cross_val_score(eclf, X, y, cv=3) |
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return scores.mean() |
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search_config = { |
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model: { |
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"n_estimators": range(10, 100, 10), |
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"max_depth": range(2, 12), |
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"hidden_layer_sizes": (range(10, 100, 10),), |
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} |
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} |
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opt = Hyperactive(search_config, n_iter=30) |
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opt.search(X, y) |
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SimonBlanke /
Hyperactive
