Hi, OBones.
1. which columns are features?
For ml,
use `setFeaturesCol` and `setLabelCol` to assign input column:
https://spark.apache.org/docs/2.1.0/api/scala/index.html#
org.apache.spark.ml.classification.DecisionTreeClassifier
2. which ones are categorical?
For ml, use Transformer to create Ve
OBones wrote:
So, I tried to rewrite my sample code using the ml package and it is
very much easier to use, no need for the LabeledPoint transformation.
Here is the code I came up with:
val dt = new DecisionTreeRegressor()
.setPredictionCol("Y")
.setImpurity("variance")
.
Hello,
I have written the following scala code to train a regression tree,
based on mllib:
val conf = new SparkConf().setAppName("DecisionTreeRegressionExample")
val sc = new SparkContext(conf)
val spark = new SparkSession.Builder().getOrCreate()
val sourceData =
spark.read.f
