无法将数据框转换为标记点 [英] Can't convert Dataframe to Labeled Point

问题描述

我的程序使用Spark.ML，我在数据帧上使用逻辑回归.但是我也想使用LogisticRegressionWithLBFGS，所以我想将数据框转换为LabeledPoint.

My program uses Spark.ML, I use logistic regression on dataframes. However I would like to use LogisticRegressionWithLBFGS too so I want to convert my dataframe into LabeledPoint.

以下代码给我一个错误

val model = new LogisticRegressionWithLBFGS().run(dff3.rdd.map(row=>LabeledPoint(row.getAs[Double]("label"),org.apache.spark.mllib.linalg.SparseVector.fromML(row.getAs[org.apache.spark.ml.linalg.SparseVector]("features")))))

错误:

org.apache.spark.ml.linalg.DenseVector cannot be cast to org.apache.spark.ml.linalg.SparseVector

所以我将SparseVector更改为DenseVector，但它不起作用:

So I changed SparseVector to DenseVector but it doesn't work :

org.apache.spark.ml.linalg.SparseVector cannot be cast to org.apache.spark.ml.linalg.DenseVector

推荐答案

您是否尝试使用org.apache.spark.mllib.linalg.Vectors.fromML代替?

Have you tried to use org.apache.spark.mllib.linalg.Vectors.fromML instead?

注意:此答案是注释中的复制粘贴，可以将其关闭.

Note: This answer is a copy paste from the comments to allow it to be closed.

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