Machine Learning Interactive Visualization

This jupyter code was created to share the model of an interactive graph to present the results of a Machine Learning Classification model.

Perfect to display the data label to extract the best interpretation of your results.

This example focuses on the prediction of bioactive compounds but it can be modified to a variety of contexts!

 

Libraries used

• pandas - a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive.

• NumPy - the fundamental package for array computing with Python

• scikit-learn - Machine Learning in Python.

• plotly - The front end for ML and data science models

Instalation

pandas:

pip install pandas

numpy

pip install numpy

scikit-learn

pip install scikit-learn

plotly

pip install plotly

Observations

This code was written by searching in different sources but mostly two answers in stackoverflow helped a lot:

• scatter-plot-markers-different-colors-based-on-value

• plotly-how-to-customize-legend

Authorship

• Author: Brenda Ferrari (brendaferrari)

Social preview original photo by Brenda Ferrari (brendaferrari)