HELP PLS: 3 datasets, Simple Voting, 3 base-member classifiers
Wiz4001
New Altair Community Member
Hello guys,
I am new to RapidMiner. Basically I have three different Datasets of 2D features (i.e. each file has 3 columns: label, feature0, feature1). I want to do an ensemble of classifiers using simple voting. Each classifier have its own dataset features as input:
1- dataset0(feature00,feature01)-->Classifier0
2- dataset1(feature10,feature11)-->Classifier1
3- dataset2(feature20,feature21)-->Classifier2
the above classifiers can be similar (such as all SVMs) or different (such as MLP, SVM, kNN, respectively). Models of these classifiers are stored and called back using (read Model).
The problem in using Rapidminer, I can only read one dataset file into the 'vote' block (similarly to the 'Apply Model').
Any one please help me in how get around this problem?
I attach a screen shot of the Main process and the Vote block:
https://dl.dropboxusercontent.com/u/50548506/Main.jpg
https://dl.dropboxusercontent.com/u/50548506/Vote.png
I appreciate your help.
Many thanks
I am new to RapidMiner. Basically I have three different Datasets of 2D features (i.e. each file has 3 columns: label, feature0, feature1). I want to do an ensemble of classifiers using simple voting. Each classifier have its own dataset features as input:
1- dataset0(feature00,feature01)-->Classifier0
2- dataset1(feature10,feature11)-->Classifier1
3- dataset2(feature20,feature21)-->Classifier2
the above classifiers can be similar (such as all SVMs) or different (such as MLP, SVM, kNN, respectively). Models of these classifiers are stored and called back using (read Model).
The problem in using Rapidminer, I can only read one dataset file into the 'vote' block (similarly to the 'Apply Model').
Any one please help me in how get around this problem?
I attach a screen shot of the Main process and the Vote block:
https://dl.dropboxusercontent.com/u/50548506/Main.jpg
https://dl.dropboxusercontent.com/u/50548506/Vote.png
I appreciate your help.
Many thanks
Tagged:
0