Metadata-Version: 2.1
Name: thompson-sampling
Version: 0.0.1
Summary: Thompson Sampling
Home-page: UNKNOWN
Author: Anton1o-I
Author-email: a.iniguez21@gmail.com
License: LICENSE.txt
Platform: UNKNOWN
Requires-Dist: typing
Requires-Dist: numpy
Requires-Dist: seaborn
Requires-Dist: matplotlib
Requires-Dist: pandas

# thompson-sampling
Thompson Sampling Multi-Armed Bandit for Python

This project is an implementation of a Thompson Sampling approach to a Multi-Armed Bandit. The goal of this project is to easily create and maintain Thompson Sampling experiments.

Currently this project supports experiments where the response follows a Bernoulli or Poisson distribution. Further work will be done to allow for experiments that follow other distributions, with recommendations/collaboration welcome.

## Usage

### Setting up the experiment:
The following method will instantiate the experiment with default priors.
```python
from thompson_sampling.bernoulli import BernoulliExperiment

experiment = BernoulliExperiment(arms=2)
```

If you want set your own priors:
```python

from thompson_sampling.bernoulli import BernoulliExperiment

experiment = BernoulliExperiment(priors=[{"a":10, "b":5}, {"a":1, "b":2}])
```

## Installation

### Pip 
```
pip install thompson-sampling
```


