similar to: .Call()

Dear mailing list, I have a C function that gives me a wrong result when I run it under Windows 7. This is the code under Linux (RHEL5): > library(phenoTest) > data(epheno) > sign <- sample(featureNames(epheno))[1:20] > score <- getFc(epheno)[,1] > head(score) 1007_s_at 1053_at 117_at 121_at 1255_g_at 1294_at -1.183019 1.113544 1.186186 -1.034779 -1.044456

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

> > > > The approach I was thinking would look something like this: > > * instead of Features, which is really a namespace implemented as a > class, we separate out the calculation of the different features > into distinct subclasses of Feature, whose only job is to calculate > a single feature. Currently the FeatureManager calls these (via >

Hello all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

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

Hello!   I would like to sample 30 % of cases (with at least 1 value lower than 3) and among them I want to set all values lower than 3 (within selected cases) as NA (NMAR- Not missing at random). I managed to sample cases, but I don’t know how to set values (lower than 3) as NA.   R code:   x <-

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

Hi all, Thank you for giving me the opportunity to work with Xapian :) I am Jiarong Wei, a third year undergraduate student in Zhejiang University, China. In GSoC 2014, I will work on Letor module with Hanxiao Sun. Here are some questions I encountered these days, 1. In letor.cc, we have two parts of functions: the training part and the ranking part. I?ll use SVMRanker as an example. The

Here is a programming question. The code I am using is quite slow and I was wondering if there is a way to get rid of the for loop. I am dealing with "interaction" in 2x2 table, and am using Edwards's G_I (Likelihood, p. 194). I label the cells in the table as follows stim response "y" "n" total -------------------------------- y hit miss nsignal

Thanks for your reply! For the third question: In https://inex.mmci.uni-saarland.de/data/documentcollection.jsp, I can find inex2010-article.qrels in 2010 assessment, but can?t find query files. Could you send me the link? I have registered on INEX website. And I also need to download ``INEX 2009 collection without annotation tags: (unofficial)`` on

Hello, I applied to letor stabilisation project for gsoc. I'd like to use coming weeks to improve the workability of xapian-letor. For that, I'm planning to refactor code in current master and begin 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

Hi~ Manu I was glad to see you were interested in Xapian, especially the learning to rank project. There are two branch in my repo. The one named gsoc2014 is followed the thought of Parth's work in which we not assign the test set for each ranking and in another one gsoc2014-evaluation we assign the training set and test set explicitly so that we can get the evaluation score of each ranking

Greeting All I am using Filebench benchmark in an "Interactive mode" to test ZFS performance with randomread wordload. My Filebench setting & run results are as follwos ------------------------------------------------------------------------------------------ filebench> set $filesize=5g filebench> set $dir=/hdd/fs32k filebench> set $iosize=32k filebench> set

Hello All, This time we are working on a weighting scheme "Learning to Rank" which involves machine learning and its a supervised ranking scheme unlike unsupervised schemes like BM25 under GSoC project. This mail intends to discuss the framework of the Learning to Rank in Xapian as a whole. I have thought of the following framework, pour in your insights or issues for the same. This is

There''s a test for activerecord called test_numeric_fields in base_test.rb. here''s the test def test_numeric_fields m = NumericData.new( :bank_balance => 1586.43, :big_bank_balance => BigDecimal("1000234000567.95"), :world_population => 6000000000, :my_house_population => 3 ) assert m.save m1 =

While doing some embedded programming and trying to figure out how to generate a hand coded SEXP equivalent of the line "t.test(x,conf.level=(1-p))$conf.int[2]" I had an idea for an addition to the embedded API. There are a number of hidden or static parse functions (R_ParseBuffer, R_Parse1Buffer, etc.) which take an IoBuffer* and returns a parsed tree. If one or more of these

Hello! I would like to sample 5 % of cases and from 1 to 3 variables within selected cases and set them as NA (MCAR-Missing completely at random). I managed to sample cases and variables, but I don’t know how to set them as NA. R code: N <- 1000      ####number of cases n <- 12           ####number of variables X <- matrix(rnorm(N * n), N, n)    ####matrix pMiss <- 0.05    

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

Here's the problem I'm trying to solve in R: I have a data frame that consists of about 1500 cases (rows) of data from kids who took a test of listening comprehension. The columns are their scores (1 = correct, 0 = incorrect, . = missing) on 140 test items. The items are numbered sequentially and are ordered by increasing difficulty as you go from left to right across the columns. I want

Hi ZFSers, I''ve been working on merging the Joyent arcstat enhancements with some of my own and am now to the point where it is time to broaden the requirements gathering. The result is to be merged into the illumos tree. arcstat is a perl script to show the value of ARC kstats as they change over time. This is similar to the ideas behind mpstat, iostat, vmstat, and friends. The current