<% from pandas_ml_utils.utils.functions import fig_to_png_base64 interpretation = { "FP Ratio": "FN/TP Ratio (should be < 0.5, ideally 0)", "FN Ratio": "FP/TP Ratio (should be < 0.5, ideally 0)", "F1 Score": "F1 Score (should be > 0.5, ideally 1)" } color = { "FP Ratio": ["green", "orange", "red"], "FN Ratio": ["green", "orange", "red"], "F1 Score": ["red","orange", "green"] } %> <%include file="../style.html"/>
<%def name="pretty_confusion_matrix(mx, fmt)">
Prediction/Truth True False
True ${fmt.format(mx[0,0])} ${fmt.format(mx[0,1])}
False ${fmt.format(mx[1,0])} ${fmt.format(mx[1,1])}

Confusion Matrix

Confusion Matrix

Confusion Loss

${pretty_confusion_matrix(summary.get_confusion_matrix(), "{:.0f}")}
${pretty_confusion_matrix(summary.get_confusion_loss(), "{:.2f}")}
% for name, value in summary.get_metrics().items(): % endfor
${interpretation[name]} ${f"{value:.2f}"}

Loss

% for target, plot in summary.plot_classification().items(): % endfor

Chart

${target or ""}