Java Deep Learning Projects

Training MLP classifier 

In Spark, an MLP is a classifier that consists of multiple layers. Each layer is fully connected to the next layer in the network. Nodes in the input layer represent the input data, whereas other nodes map inputs to outputs by a linear combination of the inputs with the node’s weights and biases and by applying an activation function.

Interested readers can take a look at https://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier.

So let's create the layers for the MLP classifier. For this example, let's make a shallow network considering the fact that our dataset is not that highly dimensional.

Let's assume that only 18 neurons in the first hidden layer and 8 neurons in ...