SAP HANA Predictive Analysis Library (PAL)

3.2.2 Back Propagation Neural Network
Neural network is a calculation model inspired by biological nervous system. The functionality of neural
network is determined by its network structure and connection weights between neurons. Back propagation
neural network (BPNN) is one of the very popular types for its training method called back propagation.
Single Neuron
A neuron takes signals from outside and transforms them to a single value as output:
●
The function F is called activate function.
● x i ( i = 1, 2, …, n ) is the outside signal and b is a constant bias usually set to 1.
●
w i ( i = 0, 1, …, n ) is the weight value on each connection.
Neural Network Structure
A neural network consists of three parts: input layer, hidden layer(s), and output layer. Each layer owns several
neurons and there are connections between layers. Signals are given in input layer and transmit through
connections and layers. Finally output layer gives transformed signals.
Steps
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 125