I'm starting to use RapidMiner after using Weka and there's one thing that is driving me crazy.
I'm using a simple dataset:http://cs.uns.edu.ar/~cic/dm2007/downloads/datasets/titanic.arff
Four nominal columns: passenger class (4 classes), age (adult or child), sex (man or woman), survived? (yes or no).
I store that data in a repository and create a very simple process: retrieve the data and apply W-Apriori operator with default parameters. No rules found message.
I don't understand how is working. In Weka GUI with the same parameters, rules are not only found but also they are right. If I insert an operator (with a multiplier) before W-Apriori and write the input to a arff file, in order to ensure what input is getting W-Apriori operator, and run Weka with that file, the same rules are obtained. I've tested with other datasets, and they aren't working either.
If I switch the algorithm to W-FPGrowth, results are consistent. Same results in Weka and in RapidMiner. I also did try to look inside of Weka plugin. I did a binary comparison between my Weka.jar and classes in the plugin. They matched completely. So I'm using exactly the same Weka version.
Does anybody know what I'm doing wrong?
I know that RapidMiner have other own operators for association rules, but all my team is working with Weka, and my first step to convince them to switch to RapidMiner is showing that all we do in Weka is directly possible in RapidMiner.
Thanks in advance!