def get_model_performance_page()

in src/responsibleai/rai_analyse/_score_card/classification_components.py [0:0]

• 58 lines of code
• 8 McCabe index (conditional complexity)

def get_model_performance_page(data):
    left_metric_elems = [p("Observe evidence of your model performance here:")]

    def get_metric_bar_plot(mname, data):
        y_0_filtermap = [
            True if i == data["classes"][0] else False for i in data["y_test"]
        ]
        y_1_filtermap = [
            True if i == data["classes"][1] else False for i in data["y_test"]
        ]
        class_0_metric = get_metric(
            mname,
            data["y_test"][y_0_filtermap],
            data["y_pred"][y_0_filtermap],
            pos_label=data["classes"][0],
            labels=data["classes"],
        )
        class_1_metric = get_metric(
            mname,
            data["y_test"][y_1_filtermap],
            data["y_pred"][y_1_filtermap],
            pos_label=data["classes"][1],
            labels=data["classes"],
        )

        y_data = [
            'Acutal "{}"'.format(data["classes"][0]),
            'Acutal "{}"'.format(data["classes"][1]),
        ]
        x_data = [int(class_0_metric * 100), int(class_1_metric * 100)]
        x_data = [[x, 100 - x] for x in x_data]

        legend = [m]
        tickvals = [0, 25, 50, 75, 100]
        ticktext = [str(x) + "%" for x in tickvals]

        png_base64 = cc.get_bar_plot(
            y_data,
            x_data,
            legend=legend,
            tickvals=tickvals,
            ticktext=ticktext,
            tickappend="%",
        )
        return div(
            img(_src="data:image/png;base64,{}".format(png_base64)),
            _class="image_div",
        )

    main_elems = []
    main_elems.append(_get_confusion_matrix_grid(data))

    for m in data["metrics"]:
        left_metric_elems.append(_get_model_performance_explanation_text(m, data))

    left_container = div(left_metric_elems, _class="left")
    main_container = div(main_elems, _class="main")
    return str(
        div(
            cc.get_page_divider("Model Performance"),
            left_container,
            main_container,
            _class="container",
        )
    )