This file contains a function called make_confusion_matrix which can be used to create a useful visualzation of a Confusion Matrix passed in as a two dimensional numpy array.
This function will make a pretty plot of an sklearn Confusion Matrix cm using a Seaborn heatmap visualization.
Arguments
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cf: confusion matrix to be passed in
group_names: List of strings that represent the labels row by row to be shown in each square.
categories: List of strings containing the categories to be displayed on the x,y axis. Default is 'auto'
count: If True, show the raw number in the confusion matrix. Default is True.
normalize: If True, show the proportions for each category. Default is True.
cbar: If True, show the color bar. The cbar values are based off the values in the confusion matrix.
Default is True.
xyticks: If True, show x and y ticks. Default is True.
xyplotlabels: If True, show 'True Label' and 'Predicted Label' on the figure. Default is True.
sum_stats: If True, display summary statistics below the figure. Default is True.
figsize: Tuple representing the figure size. Default will be the matplotlib rcParams value.
cmap: Colormap of the values displayed from matplotlib.pyplot.cm. Default is 'Blues'
See http://matplotlib.org/examples/color/colormaps_reference.html