Question
Asked 10th Mar, 2018

Which tool of Matlab (backpropagation) is best for tournament prediction?

I'm doing a mini research on predicting a certain game tournament outcome (Dota 2) using backpropagation. My data structure consists of tables of (11) team's match histories against the other 10 teams. Basically 1 set of tables for each team. The tables contains inputs of:
1. the opponent's team ID (integer value ranging 1 to 11)
2. the (5) heroes ID used by team A and (5) heroes used by team B (integer value ranging 1 to 114)
In total, the input has 11 elements.
The target tables contains values "1" if team A wins and "0" if team B wins.
I was wondering which Matlab tool is best for this problem. I had tried using the nnstart tool but I don't know how to set the tool to use backpropagation. Also I would like to know, should I normalize the data for this problem? Is binary sigmoid the correct activation function to use?
Thanks in advance.

All Answers (3)

Marc Masana
Graz University of Technology
For MatLab maybe you could consider trying MatConvNet (http://www.vlfeat.org/matconvnet/) and use it on CPU mode. For the amount of data you are proposing there probably is no need to use a GPU.
Regarding prediction of Dota 2 match outcome, I would strongly suggest using more data for each match. In order for the network to learn stuff like which heroes counter eachother, you would need more features than which position they are played on each match. In any case, I would recommend normalizing the features before feeding them to the network and you can use a sigmoid function or a cross-entropy loss for classification (output will be class 0:lose or 1:win).
Finally, in GitHub you will find several projects that try to predict Dota 2 match outcome using deep learning and that can serve as inspiration for further research.
Mohammad Behdad Jamshidi
University of Technology Sydney - The Royal Society
I suppose, there are many different kinds of approaches for prediction of tournament outcome. Although I have not had experienced on this problem, I have done a bunch of prediction works on electricity price or dynamic battery behavior by ANFIS and ANNs that are really work. You could read some of them.
1 Recommendation
Thanks for the interested question and valued answers.

Similar questions and discussions

Related Publications

Article
En esta investigación se presenta un método para el reconocimiento de personas en un canal telefónico. El cual se basa en el comportamiento de las Redes Neuronales Artificiales (RNA), en particular, sobre la arquitectura del Perceptrón Multicapa mediante el algoritmo de aprendizaje Backpropagation aunado con la aplicación de la teoría de las Wavele...
Article
The more advanced science and technology from various disciplines, currently rainfall can be predicted by carrying out various empirical approaches, one of which is by using Artificial Neural Networks (ANN). This study aims to apply ANN with backpropogation algorithm in predicting rainfall. The research data used is BPS data of the transfer city. T...
Chapter
Full-text available
Artificial Neural Network (ANN) technique was used in forecasting the Jordanian stock prices. The algorithm was developed using a feed forward multi layer neural network; the network was trained using back propagation algorithm. Software was developed by using MATLAB to simulate the performance and efficiency of the algorithm. Simulation was conduc...
Got a technical question?
Get high-quality answers from experts.