MLlib - Classification and Regression

MLlib－Classification and Regression

MLlib实现了解决二分类，多分类，回归分析问题的一些常见方法。下表具体展示了针对各个问题实现的一些方法：

Problem Type	Supported Methods
Binary Classification	linear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes
Multiclass Classification	decision trees, random forests, naive Bayes
Regression	linear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression

关于各个方法的原理以及源码实现见：

Linear models

binary classification (SVMs, logistic regression)
linear regression (least squares, Lasso, ridge)

Ensembles Decision trees

random forests
gradient-boosted trees

Naive Bayes
Isotonic regression