python：AdaBoost 分類模型

AdaBoost 分類模型 iris_adaBoost.py 

# coding=utf-8
from sklearn import datasets
from sklearn.metrics import confusion_matrix,accuracy_score
from sklearn.model_selection import train_test_split
from sklearn import preprocessing

# 加載鸢尾花資料集
iris_X,iris_y = datasets.load_iris(return_X_y=True)
# 資料預處理：按列歸一化
iris_X = preprocessing.scale(iris_X)
# 切分資料集：測試集 30%
iris_X_train,iris_X_test,iris_y_train,iris_y_test = train_test_split(iris_X,iris_y,test_size=0.3,random_state=0)
# AdaBoost 分類模型
from sklearn import ensemble
model = ensemble.AdaBoostClassifier()
# 模型訓練
model.fit(iris_X_train,iris_y_train)
# 模型預測
iris_y_pred = model.predict(iris_X_test)
# 模型評估
# 混淆矩陣
print(confusion_matrix(iris_y_test,iris_y_pred))
print("準确率: %.3f" % accuracy_score(iris_y_test,iris_y_pred))