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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

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Java Artificial Neural Network Library

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