explainx 0.7

State of the art to explain any blackbox Machine Learning model.

explainX

explainX.ai helps data scientists understand, explain and validate any machine learning model - in just one line of code. Checkout explainx.ai to learn more.

Use the package manager pip to install foobar.

pip install explainx``

## Usage

#Import the library
from explainx import *

#Load Dataset
X_data, Y_data = explainx.dataset_boston()

#Pass X_data, Y_data as numpy arrays into your XGBoost Model
model = xgboost.train({"learning_rate": 0.01}, xgboost.DMatrix(X, label=Y_data), 100)

#Pass your X_data, Y_data, y_variable name, model and model name to the explainx function
explainx.ai(X_data, Y_data, model, model_name="xgboost")

#Click on the link to access the dashboard
App running on https://127.0.0.1:8050

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT