Scikit Learn Implementation

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import numpy as np
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X = np.array([[0.5, 1.5], [1,1], [1.5, 0.5], [3, 0.5], [2, 2], [1, 2.5]])
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y = np.array([0, 0, 0, 1, 1, 1])

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from sklearn.model_selection import train_test_split
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)

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from sklearn.linear_model import LogisticRegression
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lr_model = LogisticRegression()
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lr_model.fit(X, y)

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y_pred = lr_model.predict(X)
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print("Prediction on training set:", y_pred)

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print("Accuracy on training set:", lr_model.score(X, y))