导入数据
1 | import numpy as np |
1 | from sklearn import datasets |
1 | # X[y == 0,0]:先取出y值为0的值,再取第一个属性 |
TTS实现
1 | from sklearn.model_selection import train_test_split |
三种方式实现
实现步骤:导入包,创建实例,拟合和得分
- LR
- SVM
- DT
1 | from sklearn.linear_model import LogisticRegression |
1 | 0.824 |
1 | from sklearn.svm import SVC |
1 | 0.88 |
1 | from sklearn.tree import DecisionTreeClassifier |
1 | 0.84 |
三种模型的预测
1 | y_predict1 = log_clf.predict(X_test) |
1 | # y是二分类问题,只有+1,0 |
1 | array([1, 1, 0, 0, 0, 1, 0, 1, 0, 1]) |
1 | from sklearn.metrics import accuracy_score |
1 | 0.896 |
调用sklearn接口实现
1 | from sklearn.ensemble import VotingClassifier |
1 | voting_clf.fit(X_train,y_train) |
1 | VotingClassifier(estimators=[('log_clf', |