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if not out_dfs['score_dist'].empty:
    display(HTML(out_dfs['score_dist'].to_html(index=True, classes=['alternate_colors3_groups'], float_format=float_format_func)))
else:
    (display(Markdown(no_info_str)))


    

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markdown_str = '''### Confusion matrix (human-machine) for old model ({})'''.format(experiment_id_old)


    

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if not outputs_old['df_confmatrix'].empty:
    display(Markdown(markdown_str))
    display(HTML(outputs_old['df_confmatrix'].to_html(index=True, classes=['alternate_colors2'], float_format=float_format_func)))


    

In [ ]:

    

markdown_str = '''### Confusion matrix (human-machine) for new model ({})'''.format(experiment_id_new)


    

In [ ]:

    

if not outputs_new['df_confmatrix'].empty:
    display(Markdown(markdown_str))
    display(HTML(outputs_new['df_confmatrix'].to_html(index=True, classes=['alternate_colors2'], float_format=float_format_func)))


    

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if not (outputs_new["df_confmatrix"].empty or outputs_old["df_confmatrix"].empty):
    display(Markdown('### Confusion matrix (human-machine) (change)'))
    df_change = outputs_new["df_confmatrix"] - outputs_old["df_confmatrix"]
    display(HTML(df_change.to_html(index=True, classes=['alternate_colors2'])))