autopredictor.show_all

Module Contents

Functions

show_all(result)

This function converts the trained regression model scores stored in a dictionary by

autopredictor.show_all.show_all(result)

This function converts the trained regression model scores stored in a dictionary by the “fit” function into a DataFrame, sorted alphabetically by model. It also outputs the DataFrame in a table format.

Parameters:

result (dict) – A dictionary containing scoring metrics data for each regression model. The keys represent model names where the values represent the scoring results and should be numeric.

Returns:

A DataFrame containing all scoring metrics results alongside the corresponding model, sorted alphabetically.

Return type:

DataFrame

Raises:

• TypeError – If result is not a dictionary.

• ValueError – If result dictionary is empty. If there is invalid scoring metrics in the result dictionary’s value. If the number of scoring metrics are not correct.

Examples

>>> from autopredictor.show_all import show_all
>>> model_scores = {
    'Linear Regression': {'Mean Absolute Error': 0.453,
                        'Mean Absolute Percentage Error': 0.346,
                        'R2 Score': 0.512,
                        'Mean Squared Error': 0.567,
                        'Root Mean Squared Error': 0.987},
    'Linear Regression (L1)': {'Mean Absolute Error': 61.2,
                                'Mean Absolute Percentage Error': 0.457,
                                'R2 Score': 0.239,
                                'Mean Squared Error': 0.873,
                                'Root Mean Squared Error': 72.4}
                            }
>>> test_scores = show_all(model_scores)