Introduction

Jann is a Java Artificial Neural Network library.

Background

• Started in 2011, around a year later development stopped due to work and travel.
• 9 years later, a revisit was decided, but no high expectations, only learning motivation as was in its start.

Technologies used

• Java 14 with preview features enabled
• jbom based
• jutils based

2020 Release notes

Jann v0.1.0

• Using maven
• Code clean up
• Using Java 14, Jbom, and Jutils

Legacy Release notes

JANN-0.4:

Part 1 Linear regression One/Multiple Variables Linear regression Training: Batch GD (single neuron) Stochastic GD (single or nNeurons) Feature Mapping with degrees Feature Scaling with (STD, average) Normal Equation (single neuron) Dynamic Training through Train Class Better Tests

Part 2 Models:

• Logistic Regression One Class
• Logistic Regression Multiple Classes

Training:

• Logistic Regression GD
• Regularized Linear Regression
• Regularized Logistic Regression

Utils:

• Random Initialization of theta

Part 3

Models: 1- Logistic Regression Neural Network 2- Linear Regression Neural Network

Gradient Checking Numerical Estimation of gradients Neural Network Back propagation

Part 4 Notes or Logic for Decision Making For handling errors :

1. Identify Problems with the help of (Graphs, tools)
2. Act upon on it (Manual ways, Automatic ways)

Part 5

• More Tests
• More Graphs

JANN-0.3

• Graphed Network
• Functors IFunctionable aka Java function pointers {IPerformance, Iweight, ITransfere}
• Feed forward, perceptron, backpropagation trials

JANN-0.2

• Many network structure trials
• Transfere Functions:
• COMPET
• HARDLIM
• HARDLIMS
• LOGSIG
• LOGSIGDIFF
• POSLIN
• PURELIN
• SATLIN
• SATLINS
• TANSIG
• TANSIGDIFF
• Performance Functions:
• MSE, MAE, SSE