Seleção de modelos: modelos de ensemble

Praticando perguntas de entrevista de Machine Learning em Python

Lisa Stuart

Data Scientist

Bootstrapping

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

Floresta

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

Gradient boosting

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

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

Function	returns
`sklearn.ensemble.RandomForestClassifier`	Random Forest
`sklearn.ensemble.GradientBoostingClassifier`	Gradient Boosted Model
`sklearn.metrics.accuracy_score`	trained model accuracy
`sklearn.metrics.confusion_matrix(y_test,y_pred)`	confusion matrix
`sklearn.metrics.precision_score(y_test,y_pred)`	precision
`sklearn.metrics.recall_score(y_test,y_pred)`	recall
`sklearn.metrics.f1_score(y_test,y_pred)`	f1 score

Praticando perguntas de entrevista de Machine Learning em Python