title: What do columns ‘rawPrediction’ and ‘probability’ of DataFrame mean in Spark MLlib？
body: <p>After I trained a LogisticRegressionModel, I transformed the test data DF with it and get the prediction DF. And then when I call prediction.show(), the output column names are: <code>[label | features | rawPrediction | probability | prediction]</code>. I know what <code>label</code> and <code>featrues</code> mean, but how should I understand <code>rawPrediction|probability|prediction</code>?</p>