模型選擇：集成模型

用 Python 練習機器學習面試題

Lisa Stuart

Data Scientist

自助抽樣（Bootstrapping）

自助抽樣

¹ https://medium.com/@rrfd/boosting-bagging-and-stacking-ensemble-methods-with-sklearn-and-mlens-a455c0c982de

¹ https://www.sca.com/en/about-us/our-forest/

梯度提升

¹ https://blog.bigml.com/2017/03/14/introduction-to-boosted-trees/

¹ https://scikit-learn.org/stable/modules/classes.html#module-sklearn.ensemble

函式	回傳
`sklearn.ensemble.RandomForestClassifier`	Random Forest
`sklearn.ensemble.GradientBoostingClassifier`	Gradient Boosted Model
`sklearn.metrics.accuracy_score`	訓練後模型的準確率
`sklearn.metrics.confusion_matrix(y_test,y_pred)`	混淆矩陣
`sklearn.metrics.precision_score(y_test,y_pred)`	精確率
`sklearn.metrics.recall_score(y_test,y_pred)`	召回率
`sklearn.metrics.f1_score(y_test,y_pred)`	F1 分數

用 Python 練習機器學習面試題