Free, as in open source, beer, and freedom
BorgeIt Data Mining Suite by University of Magdeburg
Techniques: apriori, bayesian network, decision trees, regression, clustering
Good for general purpose data mining
Techniques: apriori, bayesian network, decision trees, regression, clustering
Good for general purpose data mining
R by R Foundation
Techniques: linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, boosting, random forests
Seems to be for statistical research
Techniques: linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, boosting, random forests
Seems to be for statistical research
Rattle by Togaware
Techniques: apriori, decision tree, generalized linear models, oosting, random forests
General data mining application; looks simple to use
Techniques: apriori, decision tree, generalized linear models, oosting, random forests
General data mining application; looks simple to use
WEKA--The Waikato Environment for Knowledge Analysis
Techniques: Lots. decision trees, association rules, clustering, random forests, support vector machines
Java. Pretty basic interface. Looks powerful
Techniques: Lots. decision trees, association rules, clustering, random forests, support vector machines
Java. Pretty basic interface. Looks powerful
C4.5 Tutorial, Original
Techniques: C4.5 is a decision tree generating algorithm
It appears you have to compile source code in order to run the tool. Most off-the-shelf data mining tools come with a freely available implementation of the decision tree algorithm, such as WEKA
Techniques: C4.5 is a decision tree generating algorithm
It appears you have to compile source code in order to run the tool. Most off-the-shelf data mining tools come with a freely available implementation of the decision tree algorithm, such as WEKA
Non-free, as in, I'm not even going to bother trying them out
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