Dota 2 Game Outcome Predictor
Dota 2 is a popular multiplayler online battle arena (MOBA) game that puts 10 players divided into 2 teams against each other. Each player controls a unique hero with abilities and its own set of strengths and weaknesses. Our objective is to build a classifier to predict the winner of a game based on the hero matchup given a dataset containing 102,944 individual matchups and their outcomes. We'll employ the Naive Bayes algorithm as our base estimator and learn how to save the trained model for use in another process. We'll also test the model to see how well it can generalize what it has learned.
- Difficulty: Easy
- Training time: Minutes
- Memory needed: 2G
Clone the repository locally using Git:
$ git clone https://github.com/RubixML/Dota2
Install dependencies using Composer:
$ composer install
- PHP 7.1.3 or above
On the map ...
stephen.tridgell '@' sydney.edu.au
- Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.