wehub-resource-sync
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
try:
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from sklearn.model_selection import train_test_split
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except ImportError:
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from sklearn.cross_validation import train_test_split
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from sklearn.datasets import make_classification
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from mla.linear_models import LogisticRegression
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from mla.metrics import accuracy
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from mla.pca import PCA
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# logging.basicConfig(level=logging.DEBUG)
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# Generate a random binary classification problem.
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X, y = make_classification(
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n_samples=1000,
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n_features=100,
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n_informative=75,
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random_state=1111,
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n_classes=2,
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class_sep=2.5,
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)
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X_train, X_test, y_train, y_test = train_test_split(
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X, y, test_size=0.25, random_state=1111
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)
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for s in ["svd", "eigen"]:
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p = PCA(15, solver=s)
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# fit PCA with training data, not entire dataset
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p.fit(X_train)
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X_train_reduced = p.transform(X_train)
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X_test_reduced = p.transform(X_test)
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model = LogisticRegression(lr=0.001, max_iters=2500)
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model.fit(X_train_reduced, y_train)
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predictions = model.predict(X_test_reduced)
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print("Classification accuracy for %s PCA: %s" % (s, accuracy(y_test, predictions)))
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