Sentiment Analysis in Python
Violeta Misheva
Data Scientist
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123, stratify=y)
log_reg = LogisticRegression().fit(X_train, y_train)
print('Accuracy on training data: ', log_reg.score(X_train, y_train))
0.76
print('Accuracy on testing data: ', log_reg.score(X_test, y_test))
0.73
from sklearn.metrics import accuracy_score
log_reg = LogisticRegression().fit(X_train, y_train)
y_predicted = log_reg.predict(X_test)
print('Accuracy score on test data: ', accuracy_score(y_test, y_predicted))
0.73
from sklearn.metrics import confusion_matrix
log_reg = LogisticRegression().fit(X_train, y_train)
y_predicted = log_reg.predict(X_test)
print(confusion_matrix(y_test, y_predicted)/len(y_test))
[[0.3788 0.1224]
[0.1352 0.3636]]
Sentiment Analysis in Python