search for: ranklist

Hi Rishabh, I think its better not to expose RankiList to Letor.h and make it better user friendly. So my suggestion is to convert RankList to the following statement in this method. std::map<Xapian::docid, double> letor_score(const Xapian::MSet & mset); So just convert the RankList in std::map<Xapian::docid, double> format in the methods where you need to return. Parth. On Fri, Jul 27, 2012 at 5:06 PM, Rishabh Mehr...

Hi guys, I want to transfer the following code from R into .Call compatible form. How can i do that? Thanks!!! INT sim; for(i in 1:sim){ if(i>2) genemat <- genemat[,sample(1:ncol(genemat))] ranklist[,1] <- apply(genemat, 1, function(x){ (mean(x[cols]) - mean(x[-cols]))/sd(x)}) ranklist <- ranklist[order(ranklist[,1]),] if(ranklist[1,2]==1) score[i] <- 1/Ns if(ranklist[1,2]==0) score[i] <- -(1/(N-Ns)) for(j in 2:nrow(ranklist)){...

On Thu, Dec 04, 2014 at 08:28:32PM -0500, Manu Gupta wrote: > I was trying to build Han's code and was stuck here. It seems to me that > his code is trying to generate pdf for them. > > Is it possible to modify the make files to stop building the documentation. You can run the top-level configure with --disable-documentation. Cheers, Olly

...r do all the feature handling corresponding to a query. FeatureManager can have vector<Features*> FeatureList, which initialises each Feature sub-class object mentioned in the FeatureList (supplied at the time of training/ranking or as deafult set). At present, letor is mostly centred around RankList (for both training and ranking), whereas RankList is just a vector of FeatureVectors corresponding to a qid. Having RankList in ranking has no meaning since qid isn't required once the training part is over. (letor_rank(*) method in letor_internal.cc supplies a junk qid to the RankList while pe...

...improve this function. Best regards, Antonio Olinto Sao Paulo Fisheries Institute Brazil multcomp <- function(DataSet) { dat.multcomp <- DataSet names(dat.multcomp) <- c("VarCat","VarNum") attach(dat.multcomp) dat.multcomp$Rank <- rank(VarNum) attach(dat.multcomp) RankList <- aggregate(Rank,list(Rank=Rank),FUN=length) t <- length(RankList$Rank) st <- 0 for (i in 1:t) if (RankList[i,2]>1) st<-st+(RankList[i,2]^3-RankList[i,2]) LevCat <- levels(dat.multcomp$VarCat) NLevCat <- aggregate(VarCat,list(LevCat=VarCat),FUN=length) RLevCat <- aggregate(...

...tribute something. 2014-12-06 10:01 GMT+08:00 Manu Gupta <gmanu at umich.edu>: > Hi > > Thank you!! > > I tried building the letor for both the branches and unfortunately both of > them do not build : > > gsoc2014 branch gives an error at : > > C -DPIC -o .libs/ranklist.o > ranklist.cc: In member function 'void Xapian::RankList::sort_by_score()': > ranklist.cc:98:6: error: unused variable 'fvv_size' > [-Werror=unused-variable] > ranklist.cc: In member function 'void Xapian::RankList::sort_by_label()': > ranklist.cc:108:6: err...

Hi, I've read the code of letor module. And I have some questions about it: 1. In https://github.com/rishabhmehrotra/xapian/blob/master/xapian-letor/letor_internal.cc#L299, there is a write_to_file method, which save RankList into ?train.txt?. But the format for ?train.txt? is different from the one mentioned in http://trac.xapian.org/wiki/GSoC2011/LTR/Notes#QueryLevelNorm. And in https://github.com/rishabhmehrotra/xapian/blob/master/xapian-letor/letor_internal_refactored.cc#L716, Qid and DocID become optional. What for...

...from inheritance of ranker in training part just like in ranking part) 2. There is one thing I have to confirm: once we have the training model (like model file of SVMRanker), we won?t train that model again in general. (The behavior of questletor.cc under bin/ confuses me) 3. Since RankList will be removed, according to the meeting last week, its related information will be stored under MSet::Internal. My plan is to create new class under MSet::Internal. That class will have two kinds of feature vectors: normalized one and unnormalized one. Since it?s in MSet::Internal, th...

...tware/inex/, right? Thank you! Jiarong Wei On Mar 9, 2014, at 0:52, Parth Gupta <pargup8 at gmail.com> wrote: > Hi Jiarong Wei, > > > 1. In https://github.com/rishabhmehrotra/xapian/blob/master/xapian-letor/letor_internal.cc#L299, there is a write_to_file method, which save RankList into ?train.txt?. But the format for ?train.txt? is different from the one mentioned in http://trac.xapian.org/wiki/GSoC2011/LTR/Notes#QueryLevelNorm. And in https://github.com/rishabhmehrotra/xapian/blob/master/xapian-letor/letor_internal_refactored.cc#L716, Qid and DocID become optional. What for...

...writing some tests for it. Before adding tests, I think it would be better if xapian-letor could be made consistent with how xapian-core is written. For that, I'd first like to restructure some directories. Here are a few things that I intend to do: 1. Placing all api headers together (e.g. ranklist.h, letor_internal.h etc) in xapian-letor/include/letor 2. Rewriting letor.h and placing it in xapian-letor/include so that it does a job similar to xapian.h. The current letor.h contains some methods for which it is not the appropriate file. 3. Creating subdirectories like "ranker", &q...

...writes the model into a model file which can be used to rank the document. double learn_score() - Here we may calculate the score of the document using the model file with the generated vector. Flow of the program: We have to make a quest like utility say questletor, here we will get the initial ranklist in MSet. Now for each document we will get the feature values. Calculation of this features may be placed in the learn_score() method or there can be an independent method like make_feature_vector() output of which can be passed to learn_score() method. This method will return the Letor score of th...

Hi, Before starting my proposal, I wanted to know what is the expected output of Letor module. Is it for transfer learning (i.e you learn from one dataset and leverage it to predict the rankings of other dataset) or is it for supervised learning? For instance - Xapian currently powers the Gmane search which is by default based on BM25 weighting scheme and now suppose we want to use LETOR to rank