# ABAGAIL¶

The ABAGAIL library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. These are artificial intelligence algorithms implemented for the kind of people that like to implement algorithms themselves.

- Features
- Hidden Markov Models
- Feed-forward backpropagation neural networks of arbitrary topology
- Fast training with the sequential minimal optimization algorithm
- Information gain or GINI index split criteria
- Fast kd-tree implementation for instance based algorithms of all kinds
- Basic matrix and vector math, a variety of matrix decompositions based on the standard algorithms
- Randomized hill climbing, simulated annealing, genetic algorithms, and discrete dependency tree MIMIC
- Kruskals MST and DFS
- EM with gaussian mixtures, K-means
- PCA, ICA, LDA, Randomized Projections

- Installation
- Usage
- Frequently Asked Questions
- Table of contents
- What is ABAGAIL?
- How to get started with ABAGAIL?
- How is ABAGAIL project organized?
- What are the different ways to work with ABAGAIL?
- How to use ABAGAIL with Eclipse?
- Is there a tutorial or documentation for ABAGAIL?
- Can you generate graphs out of ABAGAIL library?
- How does ABAGAIL output results?
- Does Abagail have any form of built in cross validation?
- How can I find out the actual number of iterations performed in ABAGAIL?
- Could someone help explain the training_iterations in ABAGAIL? When I increase it, I get better accuracy.
- My neural network classifier is performing very poorly, how to fix it?
- How does the neural network get its weights updated?
- How to change number of neurons in a hidden layer?
- I am trying to understand what the count ones optimization function is doing, but I am not sure...
- TravelingSalesmanRouteEvaluationFunction - why the 1/total distance?
- How do I get multi-label classification working in AbaloneTest.java?
- My dataset has categorical features, can I use ABAGAIL?
- Getting ant build error: /home/unazi/ABAGAIL/build.xml:40: Unexpected attribute “additionalparam”, how do I fix this?
- What are some characteristics of problems simulated annealing works well on?