Obtaining Some Important Results
Hello
Like in WEKA, I'm used to see at the end of the training the accuracy, kapa statistics, the confusion matrix and the precision table ... I could not obtain these results with rapid miner
For example : I used the Decision Tree algorithm and I just obtained the graphical tree (not the accuracy) ... I tryed to use the precision operator but I cant use it in the same time as the decision tree operator ...
Which operator should I use and where can I put it ?
Like in WEKA, I'm used to see at the end of the training the accuracy, kapa statistics, the confusion matrix and the precision table ... I could not obtain these results with rapid miner
For example : I used the Decision Tree algorithm and I just obtained the graphical tree (not the accuracy) ... I tryed to use the precision operator but I cant use it in the same time as the decision tree operator ...
Which operator should I use and where can I put it ?
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THANK YOU SOOO MUCH !
earmijo wrote:
Ideale:
Going thru some of the sample programs provided with RM is very instructive. Take a look at the program 06_Confusion_Matrix.xml that you can find in the directory samples\Validation or 18_SimpleCostSensitiveLearning.xml in the directory samples\Learner. There you will find the answer to your question. I also recommend you go thru the RapidMiner Tutorial available from the menu Help.
Best regards,
\E
Going thru some of the sample programs provided with RM is very instructive. Take a look at the program 06_Confusion_Matrix.xml that you can find in the directory samples\Validation or 18_SimpleCostSensitiveLearning.xml in the directory samples\Learner. There you will find the answer to your question. I also recommend you go thru the RapidMiner Tutorial available from the menu Help.
Best regards,
\E