https://github.com/ericchiang/weathertweets
Machine Learning challenge from Kaggle.com.
https://github.com/ericchiang/weathertweets
Last synced: about 2 months ago
JSON representation
Machine Learning challenge from Kaggle.com.
- Host: GitHub
- URL: https://github.com/ericchiang/weathertweets
- Owner: ericchiang
- Created: 2013-10-23T14:16:47.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2013-11-07T11:19:44.000Z (over 12 years ago)
- Last Synced: 2025-09-18T00:41:19.749Z (10 months ago)
- Language: Python
- Size: 7.56 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
weatherTweets
=============
UPDATE
Please refer to my "cloudy-tweets" repo for the improved solution.
Machine Learning solution for Kaggle.com competition "Partlmy Sunny with a Chance of Hashtags"
The challenge:
Given a training set of tweets, can we extract weather information?
The Machine Learning:
Use of a customized Bag-of-Words Naive Bayes algorithm. Modifing similar algorithms for spam filters, the feature space of a given tweet is simply the set of words which comprise it, similar to an email. However, for five of the target fields in-class confidence intervals (between 0 and 1) are offered as input, and required output rather than a discrete classification (such as ham or spam).