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======= kdd2014

This is the best solution for team "Chaotic Experiments" led by Kiran R who is also the "sole team member"

#######Software Requirements###########

  1. R version 3.02 or above

  2. Ubuntu 14.04 Trusty Operating System

  3. Python 2.7

#######Data Mining Packages###########

  1. Vowpal Wabbit (any version) must be installed and the command vw must be runnable from command line meaning vw must be in the PATH variable: https://github.com/JohnLangford/vowpal_wabbit

  2. XGBoost must be installed from Tianqui Chen's repository: https://github.com/tqchen/xgboost

    1. The development version of scikit Learn installed because we use GBMs with early stopping to prevent overfitting + we want to randomly choose the number of trees at each split
  3. The following libraries must be installed in R data.table Matrix glmnet doMC foreach rbenchmark Metrics gbm RRF lme4

#####Instructions to Run the software####

  1. Copy the files in github to your local machine

  2. Set the variables in main.R correctly current_working_dir: Set to the current working directory where you place the above source files scikitLearnPath: Set to the installed location of the scikit-learn development version xgboost_path: Set to the XGBoost installed path

  3. Copy the files of the competition and unzip them to the same folder as the source files i.e. to the current_working_directory above

  4. The parts of speech features are painful to compute. So you may pick them up from here: https://www.dropbox.com/sh/fu9sx3jrdvtirlg/AAC_SrEeThn4-SxJBK2IsSzia

  5. Run source ('main.R', print.eval=T, echo=T) to run the files

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