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This package contains the scripts and sources to drive Michael
Ekstrand and John Riedl's RecSys 2012 paper “When Recommenders Fail:
Identifying and Predicting Recommender Failure for Evidence-Based
Algorithm Selection and Combination”.

Dependencies:

- LensKit 0.11-SNAPSHOT, from https://bitbucket.org/elehack/lenskit,
  revision f0215b1985f2 with the lenskit-clamp-predictors.patch patch
  (in this package) applied.

- Java 6 and Maven 3

- R (tested with 2.14.2; requires a version with the 'parallel' package)

- R packages
  - doBy
  - xtable
  - ROCR
  - ggplot2

- Emacs with Org-Mode 7.8.0 (to re-export the R scripts)

To run:

1. Clone LensKit
   hg clone -r f0215b1985f2 https://bitbucket.org/elehack/lenskit

2. Apply the patch (in LensKit dir)
   patch -p1 <../error-analysis/lenskit-clamp-predictors.patch

3. Install LensKit (in LensKit dir)
   mvn install

4. Download the ML-10M data set from http://grouplens.org/node/73 and
   unpack it into a directory called ‘ml-10m’ (the 'ratings.dat' file
   should reside directly in ‘ml-10m’).

5. Compile & build the add-on code
   mvn package

6. Import the MovieLens ratings into a Lucene index
   ./target/dist/bin/import-tags ml-10m/movies.dat ml-10m/tags.dat ml-10m.idx

7. Run the recommenders (-j4 uses 4 threads)
   ./target/dist/bin/lenskit-eval -j4 lenskit.groovy

8. Run the R scripts (runs with library & data load dependencies)
   cd paper && ./run-R.pl *.R

9. Build the paper in paper/error-analysis-short.tex (requires
   PDFLaTeX and BibTeX)


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