Notebook for data science autoselect.

This is an experimental Project. The aim of this library is to autoselect visuaizations to evaluate machine learning models.

Import the library

You can import th library locally i from this repo via

import vis_autselect.visualize as visualize

Instatiate a visualizer object:

vis = visualize.Visualizer()

Input data with the select function

You can import data in two different ways

1. Pass in an output array from your ml experiment vis.select(some_arr)
2. Pass in an annotated array to help classify the input data vis.input_dict({'Confidence Scores': y_score})

There is also the possibillity to import multiple object as such:

annotaded_data = {
    'Confidence Scores': y_score, 
    'Confusion Matrix' : cm,
    'ROC' : roc,
    'Ground Truth Values' : y_test, 
    'Predictions' : y_pred
}

vis.input_dict(annotaded_data)

Get info about the classified data

vis.info()

Visualize Experimental Feature

After you have inputed all the data you can just call the visualize() function and it will generated all possible vissualizations.

Try it yourself and explore examples