File	Date	Author	Commit
.github	2019-09-17	Anton Antonov	[7c4122] Update issue templates
Applications	2018-05-18	antononcube	[d21f9c] Importing QuantileRegression.m only if needed.
Data	2019-12-17	antonocube	[dde297] Minor formatting for easier text ingestion.
Documentation	2020-02-25	antonocube	[38369d] Better typography and explanations.
EBNF	2017-05-19	antononcube	[b3c26e] Making the EBNF spec Get-able.
Examples	2018-07-09	antononcube	[14d618] Better layout.
Java	2017-11-30	Anton Antonov	[470350] Implemented topRootToLeafPaths and supporting f...
Lua	2016-03-16	Anton Antonov	[eb6a90] Corrected references.
MarkdownDocuments	2020-12-28	antonocube	[7ba4ac] First version.
Misc	2021-02-03	antonocube	[76f48e] Allowing LearnedDistribution to be used in gene...
MonadicProgramming	2021-04-22	antonocube	[b6e388] fix: Using number of recommendations argument i...
Notebooks	2019-07-31	antonocube	[a0ae6c] Better names.
OPL	2018-07-22	Anton Antonov	[20ec6d] Minor changes.
R	2019-07-07	antonocube	[4641dd] Bug fix.
UnitTests	2021-02-03	antonocube	[55d00a] Bug fix.
AVCDecisionTreeForest.m	2017-06-30	Anton Antonov	[4eeb6b] Small typographical changes.
AprioriAlgorithm.m	2019-11-05	antonocube	[637088] Minor code syntax improvements.
AprioriAlgorithmV9.m	2014-10-30	Anton Antonov	[776dba] Snapshot of Apriori algorithm implementation wi...
BiSectionalKMeans.m	2020-02-22	antonocube	[38dc87] Implementation of labeled sparse arrays.
ChernoffFaces.m	2019-11-10	antonocube	[937ec3] Better usage message for ChernoffFace.
ClassifierEnsembles.m	2020-10-20	antonocube	[617662] Revert.
CrossTabulate.m	2019-10-07	antonocube	[ebdbba] Reverted to producing sparse matrices by defaul...
DataReshape.m	2020-11-16	antonocube	[2ca62f] Added LongFormDataset and WideFormDataset as sy...
DocumentTermMatrixConstruction.m	2020-09-23	antonocube	[72dde1] Allowing stopWords to be None.
FunctionalParsers.m	2019-08-26	antonocube	[727776] Minor code syntax improvements.
IndependentComponentAnalysis.m	2019-10-12	antonocube	[269bee] Better code.
JavaTriesWithFrequencies.m	2019-10-24	antonocube	[7acc69] Minor code syntax improvement.
LICENSE	2017-01-11	Anton Antonov	[ba013d] GPL 3.
MathematicaForPredictionUtilities.m	2021-03-29	antonocube	[9e4060] Added Method option to ImportCSVToDataset.
MosaicPlot.m	2019-10-01	antonocube	[e15d43] Minor code syntax corrections.
MosaicPlotV9.m	2018-05-23	antononcube	[3a31f2] Better the context names.
NGramMarkovChains.m	2014-09-08	Anton Antonov	[1364f5] More robust implementation of the generation fu...
NGramMarkovChainsV9.m	2014-09-08	Anton Antonov	[7f5589] Moved the implementation of for Version 9 into ...
NaiveBayesianClassifier.m	2013-10-20	Anton Antonov	[391228] Added implementations of NBCClassificationSucce...
NonNegativeMatrixFactorization.m	2019-12-19	antonocube	[e34d12] Bug fix.
OutlierIdentifiers.m	2020-09-24	antonocube	[d439cb] Defined shortcut functions.
ParetoPrincipleAdherence.m	2019-12-05	antonocube	[0594bc] First version.
QuantileRegression.m	2019-10-17	antonocube	[d55790] Better QuantileRegressionFit.
README	2019-09-17	antonocube	[294078] Updated version.
README.md	2019-09-17	antonocube	[294078] Updated version.
ROCFunctions.m	2021-02-05	antonocube	[6cb4c6] Minor code syntax changes.
SSparseMatrix.m	2021-03-22	antonocube	[21e5cf] Added ToSSparseMatrix implementation for an ass...
SparseMatrixRecommenderFramework.m	2018-09-01	Anton Antonov	[41801b] Added implementation of recommendations by tags...
TriesWithFrequencies.m	2021-03-16	antonocube	[cf1305] Added/surfaced ToTrieWithRoot and TrieBlank.
TriesWithFrequenciesV9.m	2018-05-23	antononcube	[3a31f2] Better the context names.
VariableImportanceByClassifiers.m	2018-05-04	antononcube	[729141] Changed the option "Classes" to "ClassLabeles".

Read Me

(This README is OBSOLETE; see the Markdown one: https://github.com/antononcube/MathematicaForPrediction/blob/master/README.md . )

This open source project is for Mathematica implementations of machine learning algorithms that are used or can be used for prediction and personalization systems.
(For prediction and facilitation of the behaviour of users, customers, clients, etc.)

The algorithms implementations are given in Mathematica package files ("*.m").
Explanations or presentations about the algorithms are given in Mathematica notebook files ("*.nb").

The original set of algorithms is:
1. k-means and bisecting k-means;
2. associative rules finding;
3. decision trees and random forests;
4. non-negative matrix factorization;
5. prefix trees;
6. naive Bayesian classifiers generator;
7. a framework for linear vector space representations of document collections;
8. an item-item recommender framework based on sparse linear algebra.

In the future are going to be added algorithms for 
9. quantile regression,
10. self-organizing maps,
11. hierarchical clustering,
12. n-gram language models.

Also in this repository are going to be placed example or demonstrations notebooks for different applications of the algorithms listed above.

There is a blog associated with this project: http://mathematicaforprediction.wordpress.com .

I have implemented and extensively used these algorithms in search and prediction engines work in the last 5.5 years.

Anton Antonov
04.07.2013, Florida, USA