Does Spark.ml LogisticRegression assumes only Double valued features?

Hi, I was looking at the `Spark 1.5` dataframe/row api and the implementation for the logistic regression

Re: Does Spark.ml LogisticRegression assumes only Double valued features?

When you pass a data frame into the train method of LogisticRegression and other ML learning algorithms, the data is extracted by using parameters `labelCol` and `featuresCol` which should have been set before calling the train method (they default to "label" and "features", respectively). `feature