Re: how to construct parameter for model.transform() from datafile

Just found that you can specify number of features when loading libsvm source: val df = spark.read.option("numFeatures", "100").format("libsvm") Liang-Chi Hsieh wrote > As the libsvm format can't specify number of features, and looks like > NaiveBayes doesn't have such parameter, if your

Re: how to construct parameter for model.transform() from datafile

As the libsvm format can't specify number of features, and looks like NaiveBayes doesn't have such parameter, if your training/testing data is sparse, the number of features inferred from the data files can be inconsistent. We may need to fix this. Before a fixing going into NaiveBayes,

Re: how to construct parameter for model.transform() from datafile

Hi Jinhong, Based on the error message, your second collection of vectors has a dimension of 804202, while the dimension of your training vectors was 144109. So please make sure your test dataset are of the same dimension as the training data. >From the test dataset you posted, the vector

Re: how to construct parameter for model.transform() from datafile

Anyone help? > 在 2017年3月13日，19:38，jinhong lu 写道： > > After train the mode, I got the result look like this: > > > scala> predictionResult.show() > > +-++++--+ > |label|

Re: how to construct parameter for model.transform() from datafile

After train the mode, I got the result look like this: scala> predictionResult.show() +-++++--+ |label|features| rawPrediction| probability|prediction|