Lazy Predict: Explore lots of machine learning models at once

The Lazy Predict module in Python is a library that allows users to quickly and easily create predictive models from data. It provides a simple API for creating and training models, as well as a set of tools for evaluating and optimizing them. An example of using the Lazy Predict module would be to create a model to predict the price of a house based on its size, location, and other features. The user would first create a model using the Lazy Predict API, then train it on a dataset of house prices. Finally, the user would use the tools provided by the module to evaluate and optimize the model, and then use it to make predictions on new data.

Example

Here is a simple example of how Lazy Predict can be used:

Considering the breast cancer dataset, let’s test lots of models on this dataset with Lazy Predict.

And here is the output:

Reference

[1] Lazy Predict