Look at LinkedIn's Photon ML package: https://github.com/linkedin/photon-ml
One of the caveats is/was that the input data has to be in Avro in a
specific format.
On Mon, Mar 26, 2018 at 1:46 PM, Josh Goldsborough <
joshgoldsboroughs...@gmail.com> wrote:
> The company I work for is trying to do s
;
> scala> val indexer = new StringIndexer().setInputCol(
> featureCols).setOutputCol("categoryIndex").fit(df1)
> :29: error: type mismatch;
> found : Array[String]
> required: String
> val indexer = new StringIndexer().setInputCol(
> featureCols).setOutp
I don't think it does. From the documentation:
https://spark.apache.org/docs/2.0.0-preview/ml-features.html#onehotencoder,
I see that it still accepts one column at a time.
On Wed, Aug 17, 2016 at 10:18 AM, janardhan shetty
wrote:
> 2.0:
>
> One hot encoding currently accepts single input column
