Re: How VectorIndexer works in Spark ML pipelines

Vishnu, VectorIndexer will add metadata regarding which features are categorical and what are continuous depending on the threshold, if there are more different unique values than the *MaxCategories *parameter, they will be treat

How VectorIndexer works in Spark ML pipelines

HI All, I am trying to use the VectorIndexer (FeatureExtraction) technique available from the Spark ML Pipelines. I ran the example in the documentation . val featureIndexer = new VectorIndexer() .setInputCol("features") .setOutputCol("indexedFeatures") .setMaxCategories(4) .fit(data)