Scikit-Learn

Let’s work with logistic models using scikit-learn

import numpy as np

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

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Fit the Model

• We will first import the model
• Then we’ll fit the model to the training data by calling fit()

from sklearn.linear_model import LogisticRegression

lr_model = LogisticRegression()
lr_model.fit(X, y)

LogisticRegression()

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Make Predictions

y_pred = lr_model.predict(X)

print("Prediction on training set:", y_pred)

Prediction on training set: [0 0 0 1 1 1]

Calculate Accuracy

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

Accuracy on training set: 1.0