Using data from Taarifa and the Tanzanian Ministry of Water, can you predict which pumps are functional, which need some repairs, and which don't work at all? This is an intermediate-level practice competition. Predict one of these three classes based on a number of variables about what kind of pump is operating, when it was installed, and how it is managed. A smart understanding of which waterpoints will fail can improve maintenance operations and ensure that clean, potable water is available to communities across Tanzania.
This repository contains code volunteered from leading competitors in the Pump it Up: Data Mining the Water Table on DrivenData.
| Team or User | Score | Date of Rank | Rank | Folder | Programming Language |
|---|---|---|---|---|---|
| madRid | 0.8265 | 2017-01 | 5 | madRid | R |
| benedekrozemberczki | 0.8264 | 2017-01 | 6 | benedekrozemberczki | R |
| mrbeer | 0.8243 | 2017-01 | 20 | mrbeer | Python |
| mattiaf | 0.8238 | 2017-01 | 24 | mattiaf | Python |
| dipetkov | 0.8215 | 2017-01 | 54 | dipetkov | R |
| bhagyeshvikani | 0.8205 | 2017-01 | 84 | bhagyeshvikani | Python |
| aratik | 0.8122 | 2017-01 | 226 | aratik | R |
| kamchatang | 0.8073 | 2017-01 | 268 | kamchatang | Python |
| Hammer Data Project | 0.7688 | 2017-01 | 493 | [Hammer Data Project](Hammer\ Data\ Project) | R |
If you're competing and want your work included, submit a pull request.