Welcome to EasyPred’s documentation!
What is it?
EasyPred is a Python package to easily store, analyse, assess and compare predictions from Machine Learning and Data Mining models.
The package allows to create different types of model-agnostic prediction objects simply by passing real and fitted data. These objects have properties and methods that return various accuracy and error metrics, together with relevant plots.
Why EasyPred can be useful:
All-in-one bundle: having data and accuracy metrics in a single object means less stuff you need to keep an eye on
Minimize code redundancy: pass the data once and get all the information and metrics you want
Easy and flexible comparison: create the predictions first and then decide what to compare. Changed your mind? The object is there, simply access another method