- author = "Aleksandra Takac",
- title = "Genetic Programming in Data Mining - Cellular Approach",
- school = "Institute of Informatics Faculty of Mathematics, Physics and Informatics, Comenius University",
- year = "2003",
- address = "Bratislava, Slovakia",
- month = apr,
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://www.ii.fmph.uniba.sk/~takaca/thesis/thesis.pdf",
- size = "70 pages",
-
notes = "First results will be here soon of cellular genetic
programming on classification task on 3 different
datasets (from the link above): German Credit,
Australian Credit and Heart disease. Here is another
very good link with dataset links : Datasets for Data
Mining Also I recommend this very good website for
datamining and knowledge discovery:
http://www.kdnuggets.com/
The test I perform uses sql queries for evaluating individuals of population, genetic programing model is cellular, 2 types of attributes are considered continuous and qualitative. In all examples are 2 classes, the results can be compared to other algorithms that were in the project STATLOG. Method for testing the algorithm is 10 and 9-Fold Cross Validation.
(01/04/2003)
The experiment and results of classification task with cellular genetic programming.
(05/04/2003)
Third chapter - Data Mining",
