Multilayer perceptron classifier

A multilayer perceptron classifier (MLPC) is a feedforward artificial neural network with multiple layers of nodes connected to each other in a directed fashion. It uses a supervised learning technique called backpropagation for training the network.

Nodes in the intermediary layer use the sigmoid function to restrict the output between 0 and 1, and the nodes in the output layer use the softmax function, which is a generalized version of the sigmoid function.

Scala:

scala> import org.apache.spark.ml.classification.MultilayerPerceptronClassifier
import org.apache.spark.ml.classification.MultilayerPerceptronClassifier
scala> import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
scala> import org.apache.spark.mllib.util.MLUtils
import org.apache.spark.mllib.util.MLUtils

// Load training data
scala> val data = MLUtils.loadLibSVMFile(sc,
"data/mllib/sample_multiclass_classification_data...