technical question about the combined use of clustering and classification
Hi there! I'm a newbie to rapidminer and confronted a problem regarding the combined use of the clustering and classification.
Basically, I want to develop k-means clusters of my initial dataset and then further build models to perform the classification and evaluate their performance for EACH of the clusters. I know how to use the operators to perform cluster analysis and classification respectively but have no idea how to deploy the operators to combine them. I tried many ways such as placing the k-means operators before or within the cross-validation but still fail to either run it successfully or get the performance result of each cluster. Can anyone help?
Any response would be greatly appreciated
Thank you!
Basically, I want to develop k-means clusters of my initial dataset and then further build models to perform the classification and evaluate their performance for EACH of the clusters. I know how to use the operators to perform cluster analysis and classification respectively but have no idea how to deploy the operators to combine them. I tried many ways such as placing the k-means operators before or within the cross-validation but still fail to either run it successfully or get the performance result of each cluster. Can anyone help?
Any response would be greatly appreciated
Thank you!