[Solved] R script loses data (kMed -
Smerg
New Altair Community Member
Hello people,
I'm desperate. For weeks I've been working on the process. After several remodeling and many attempts, it still does not work.
In my stand alone version, everything works fine. In my whole process with loops, an error appears: "The attribute "hungarian cluster" does not exist.... ", because my R script loses the data. So it's clear, that the following operator can not find an attribute.
My if statement in R intervenes. The error emerges in the fourth pass of inner loop and generate this error. The log says: "PM INFO: Hungarian Algorithm: Fehler in minWeightBipartiteMatching(clusterA, clusterB) : number of cluster or number of instances do not match"
Why it works the first three repetitions?! I hope you can help me!
Download
Error version of my process: https://dl.dropbox.com/u/5861880/Error_version.xml
Working minimal version without loops: https://dl.dropbox.com/u/5861880/Working_version.xml
Example set
I use the wine dataset from UCI: http://archive.ics.uci.edu/ml/datasets/Wine.
What do I want?
I'm desperate. For weeks I've been working on the process. After several remodeling and many attempts, it still does not work.
In my stand alone version, everything works fine. In my whole process with loops, an error appears: "The attribute "hungarian cluster" does not exist.... ", because my R script loses the data. So it's clear, that the following operator can not find an attribute. My if statement in R intervenes. The error emerges in the fourth pass of inner loop and generate this error. The log says: "PM INFO: Hungarian Algorithm: Fehler in minWeightBipartiteMatching(clusterA, clusterB) : number of cluster or number of instances do not match"
Why it works the first three repetitions?! I hope you can help me!
Download
Error version of my process: https://dl.dropbox.com/u/5861880/Error_version.xml
Working minimal version without loops: https://dl.dropbox.com/u/5861880/Working_version.xml
Example set
I use the wine dataset from UCI: http://archive.ics.uci.edu/ml/datasets/Wine.
What do I want?
- 10 splits of D to Dtraining and Dtest. I repeat it for k = 3 to 20
- For every split, I choose ten times k examples for every predefined cluster.
- For every inner loop, I run k-medois and relabel the training data with the hungarian method in R. For this purpose I use the k previously selected examples per cluster and optimize they. This bases on mapping computated cluster and predefined cluster.
- Afterwards I measure the performance of my SVM-Model with Dtest
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