基於scikit-learn的簡單邏輯回歸（Logistic regression）練習

#用邏輯回歸解決該問題
from sklearn.linear_model import LogisticRegression as LR
from sklearn.linear_model import RandomizedLogisticRegression as RLR
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split

X = train_data
Y = target

#無需進行分組，數據自行划分為測試集和訓練集
# X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=0)

#歸一化
sc=StandardScaler().fit(X_train)
X_train_std = sc.transform(X_train)
X_test_std = sc.transform(X_test)

lr = LR()
lr.fit(X_train,Y_train)

pred_test = lr.predict_proba(X_test)
acc=lr.score(X_test,Y_test)

# result.to_csv('submission_result')