问题
I'm training a NaiveBayesModel in Spark, however when I'm using it to predict a new instance I need to get the probabilities for each class. I looked at the code of predict function in NaiveBayesModel and come up with the following code:
val thetaMatrix = new DenseMatrix (model.labels.length,model.theta(0).length,model.theta.flatten,true)
val piVector = new DenseVector(model.pi)
//val prob = thetaMatrix.multiply(test.features)
val x = test.map {p =>
val prob = thetaMatrix.multiply(p.features)
BLAS.axpy(1.0, piVector, prob)
prob
}
Does this work properly? The line BLAS.axpy(1.0, piVector, prob)
keeps giving me an error that the value 'axpy' is not found.
回答1:
In a recent pull-request this was added to the Spark trunk and will be released in Spark 1.5 (closing SPARK-4362). you can therefore call
def predictProbabilities(testData: RDD[Vector]): RDD[Vector]
or
def predictProbabilities(testData: Vector): Vector
来源:https://stackoverflow.com/questions/31842502/how-to-get-the-probabilities-of-classes-in-spark-naive-bayes-classifier