分类(Classification) 下面的例子说明了怎样导入LIBSVM 数据文件,解析成RDD[LabeledPoint],然后使用决策树进行分类.GINI不纯度作为不纯度衡量标准并且树的最大深度设置为5.最后计算了测试错误率从而评估算法的准确性. from pyspark.mllib.regression import LabeledPoint from pyspark.mllib.tree import DecisionTree, DecisionTreeModel from pyspa
1.什么是MLBaseMLBase是Spark生态圈的一部分,专注于机器学习,包含三个组件:MLlib.MLI.ML Optimizer. ML Optimizer: This layer aims to automating the task of ML pipeline construction. The optimizer solves a search problem over feature extractors and ML algorithms included inMLI and