RandomForestClassifier

Supports both binary and multiclass labels, as well as both continuous and categorical features.

Input

Takes in a DataFrame and performs Random Forest Classification

Output

Random Forest Classification Model generated is passed along to the next nodes. The input DataFrame is also passed along to the next nodes

Type

ml-estimator

Class

fire.nodes.ml.NodeRandomForestClassifier

Fields

Details

Random forests supports both binary and multiclass labels, as well as both continuous and categorical features.

More at Spark MLlib/ML docs page : http://spark.apache.org/docs/latest/ml-classification-regression.html#random-forest-classifier