To answer more accurately to your question, the model.fit(df) method takes in a DataFrame of Row(label=double, feature=Vectors.dense([...])) .
cheers, Ardo. On Tue, Jun 21, 2016 at 6:44 PM, Ndjido Ardo BAR <ndj...@gmail.com> wrote: > Hi, > > You can use a RDD of LabelPoints to fit your model. Check the doc for more > example : > http://spark.apache.org/docs/latest/api/python/pyspark.ml.html?highlight=transform#pyspark.ml.classification.RandomForestClassificationModel.transform > > cheers, > Ardo. > > On Tue, Jun 21, 2016 at 6:12 PM, pseudo oduesp <pseudo20...@gmail.com> > wrote: > >> Hi, >> i am pyspark user and i want test Randomforest. >> >> i have dataframe with 100 columns >> i should give Rdd or data frame to algorithme i transformed my dataframe >> to only tow columns >> label ands features columns >> >> df.label df.features >> 0 (517,(0,1,2,333,56 ... >> 1 (517,(0,11,0,33,6 ... >> 0 (517,(0,1,0,33,8 ... >> >> but i dont have no ieda to transorme data frame like input to data frame >> i test the example in offciel web page without succes >> >> please give me example how i can work and specily with test set . >> >> thanks >> > >
