- [Inductive Programming]
IP 1.3 (IP_1.3).
-
- IP.hs --for convenience,
IP collects up the other modules IP/ :
- CTrees.hs
--classification- (decision-), model- and regression-trees.
- MixtureModels.hs
--mixture modelling (clustering).
- Models.hs
--example models (probability distributions).
- T.hs
--Student's t Distribution (is a Model).
- FnModels.hs
--example function models (regressions).
- TSModels.hs
--example time-series models.
- Classes.hs
--class definitions for various sorts of statistical-model.
- Utilities.hs
--like it says.
- Sci.hs
--some useful scientific/numerical functions.
-
- Test/
--directory, contains test programs for the IP modules;
Test/Blah.hs is a test for IP/Blah.hs
- ghc --make Test/Blah
--compiles a test
- Example/
--directory, contains illustrative
example programs for the IP modules.
- ghc --make Example/Blah
--compiles an example
- Data/
----directory, contains data for use with example programs.
-
Selected References
- L. Allison,
Models for machine learning and data mining in functional programming,
J. Functional Programming (JFP), 15(1), pp.15-32,
[doi:10.1017/S0956796804005301],
January 2005.
-
- L. Allison,
A Programming Paradigm for Machine Learning, with a Case Study of
Bayesian Networks,
ACSC2006, pp.103-111, January 2006.
-
- M. B. Dale, L. Allison, and P. E. R. Dale,
Segmentation and Clustering as Complementary Sources of Information,
Acta Oecologica, 31(2), pp.193-202,
[doi:10.1016/j.actao.2006.09.002]
March-April 2007.
-
- L. Allison,
Added Distributions for use in Clustering (Mixture Modelling),
Function Models, Regression Trees, Segmentation, and
mixed Bayesian Networks in
Inductive Programming 1.2. (IP 1.2)
TR 2008/224,
Faculty of IT, Monash U.,
April 2008.