WEKA Sample Execution java weka.associations.Apriori -t data/weather.nominal.arff -I yes Apriori ======= Minimum support: 0.2 Minimum confidence: 0.9 Number of cycles performed: 17 Generated sets of large itemsets: Size of set of large itemsets L(1): 12
WEKA Boosting ADA Boost Logit Boost Decision Stump
WEKA Pros and Cons of WEKA Covers the Entire Machine Learning Process Easy to compare the results of the different algorithms implemented Accepts one of the most widely used data formats as input i.e the ARFF format.
WEKA Pros and Cons for WEKA Flexible APIs for programmers Customization possible
WEKA Pros and Cons for WEKA Textual User Interface Requires the Java Virtual Machine to be installed for execution Visualization of the mining results not possible
WEKA Enhancements The new version of WEKA 3.1.7 overcomes some of the decripancies of the previous version like –Graphical User Interface –Visualization of Results. –Mining of Non - local data bases