Batcar
is a tool for evaluating model through time in order to narrow the gap between research and deployment. Batcar evaluates & updates model through time just like in real situation
- For business
- Persuade need of continual learning by showing result when it's applied/not applied
- Investigate amount of data needed for training by monitoring model performance
- For analysis
- Investigate distribution changes (trend / seasonality) by monitoring model performance
- For research
- Compare different update triggers
- Compare different model update methods
import batcar
batcar = BatCar()
batcar.drive(x, y, model)
model_archive = batcar.history['models']
history_pred = batcar.history['pred']
history_eval = batcar.history['eval']
- x, y
- nd.ndarray or pd.DataFrame, pd.Series
- supports pd.RangeIndex, pd.Int64Index, pd.DatetimeIndex
- model
- should be able to train with .fit()
- should be able to predict with .predict()
$ git clone https://github.com/makinarocks/batcar.git
...
# Update document when code changes
pip3 install pdoc3
pdoc3 --html batcar --force
mv html/batcar docs
rm -r html
content