Re: How can I use pyspark.ml.evaluation.BinaryClassificationEvaluator with point predictions instead of confidence intervals?

SOLVED. The rawPredictionCol input to BinaryClassificationEvaluator is a vector specifying the prediction confidence for each class. Since we are talking about binary classification the prediction for class 0 is simply (1 - y_pred), where y_pred is the prediction for class 1. So this can be

How can I use pyspark.ml.evaluation.BinaryClassificationEvaluator with point predictions instead of confidence intervals?

pyspark.ml.evaluation.BinaryClassificationEvaluator expects predictions in the form of vectors (apparently designating confidence intervals), as described in https://spark.apache.org/docs/latest/api/python/pyspark.ml.html#pyspark.ml.evaluation.BinaryClassificationEvaluator However, I am trying to