Scikit Learn Implementation

记录scikit learn库的使用~~~

Logistic Regression

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Loading Dataset

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])

Split the train/test set

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)

Fit the Model

from sklearn.linear_model import LogisticRegression

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

Make Predictions

y_pred = lr_model.predict(X)

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

Evaluate Accuracy

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