data-mining

I have just computed PCA on a training set and Weka returned me the new attributes with the way in which they were selected and computed. Now, I want to build a model using these data and then use the model on a test set. Do you know if there is a way to automatically modify the test set according to the new type of attributes? Do you need the principal components for analysis or just to feed into the classifier? If not just use the Meta->FilteredClassifier classifier. Set the filter to PrincipalComponents and and the classifier to whatever classifier you want to use. Train it on the un

I am researching sparse adjacency matrices where most cells are zeros and some ones here-and-there, each relationship between two cells has a polynomial description that can be very long and their analysis manually time-consuming. My instructor is suggesting purely algebraic method in terms of Gröbner bases but before proceeding I would like to know from purely computer science and programming perspective about how to analyse sparse adjacency matrices? Does there exist some data mining tools to analyse them? hhh Multivariate polynomial computation and Gröbner basis is an active research area.

I've just used Weka to train my SVM classifier under "Classify" tag. Now I want to further investigate which data samples are mis-classified,I need to study their pattern,but I don't know where to look at this from Weka. Could anyone give me some help please? Thanks in advance. You can enable the option from: You will get the following instance predictions: === Predictions on test split === inst# actual predicted error prediction 1 2:Iris-ver 2:Iris-ver 0.667 ... 16 3:Iris-vir 2:Iris-ver + 0.667 EDIT As I explained in the comments, you can use the StratifiedRemoveFolds filter to manually split

I have some sentences, from the sentences I want to separate the words to get row vector each. But the words are repeating to match with the largest sentence's row vector that I do not want. I want no matter how large the sentence is, the row vector of each of the sentences will only be the words one time. sentence <- c("case sweden", "meeting minutes ht board meeting st march now also attachment added agenda today s board meeting", "draft meeting minutes board meeting final meeting minutes ht board meeting rd april") sentence <- cbind(sentence) word_table <- do.call(rbind, strsplit(as

In my program, i'm taking k=2 for k-mean algorithm i.e i want only 2 clusters. I have implemented in a very simple and straightforward way, still i'm unable to understand why my program is getting into infinite loop. can anyone please guide me where i'm making a mistake..? for simplicity, i hav taken the input in the program code itself. here is my code : import java.io.*; import java.lang.*; class Kmean { public static void main(String args[]) { int N=9; int arr[]={2,4,10,12,3,20,30,11,25}; // initial data int i,m1,m2,a,b,n=0; boolean flag=true; float sum1=0,sum2=0; a=arr[0];b=arr[1]; m1=a;

I've recently discovered RapidMiner, and I'm very excited about it's capabilities. However I'm still unsure if the program can help me with my specific needs. I want the program to scrape xpath matches from an URL list I've generated with another program. (it has more options then the 'crawl web' operator in RapidMiner) I've seen the following tutorials from Neil Mcguigan: http://vancouverdata.blogspot.com/2011/04/web-scraping-rapidminer-xpath-web.html . But the websites I try to scrape have thousands of pages, and I don't want to store them all on my pc. And the web crawler simply lacks