逻辑回归：再访

Python 中的情感分析

Violeta Misheva

Data Scientist

复杂模型与正则化

from sklearn.linear_model import LogisticRegression

# Regularization arguments
LogisticRegression(penalty='l2', C=1.0)

log_reg = LogisticRegression().fit(X_train, y_train)

# Predict labels 
y_predicted = log_reg.predict(X_test)

# Predict probability
y_probab = log_reg.predict_proba(X_test)

y_probab
array([[0.5002245, 0.4997755],
       [0.4900345, 0.5099655],
        ...,
       [0.7040499, 0.2959501]])

# Select the probabilities of class 1
y_probab = log_reg.predict_proba(X_test)[:, 1]

array([0.4997755, 0.5099655 ..., 0.2959501]])

# 默认概率阈值编码：
# 若概率 >= 0.5，则为类别 1；否则为类别 0

Python 中的情感分析