The code contains implementation of an entry to GECCO 2015 Industrial Challenge. The methodology used in the implementation is documented in methodology.md and a pdf report.
For more information regarding the competition, please refer to http://www.spotseven.de/gecco-challenge/gecco-challenge-2015/.
To reproduce the entry, first install the required packages in R:
install.packages(c("timeDate", "lubridate", "xts", "e1071", "gramEvol", "Metrics", "memoise"))Run train-all.R to cross-validate and select prediction models:
source("train-all.R")The models will be stored in the models directory. As this process is slow (a runtime of 2 days on a 4.0 GHz Intel Core i7-4790 was observed), the selected models were stored and are distributed with the source code.
To generate the prediction csv file, run:
source("pred-all.R")Feel free to open an issue in github or contact the author at:
- Farzad Noorian [email protected]
All files in this package are free software; you can redistribute them and/or modify them under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
These files are distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with these files; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA, or visit https://www.gnu.org/licenses/gpl-2.0.html.