Plot Confusion Matrix
Visualize the performance of your Machine Learning model with a confusion matrix. It is a fundamental tool in evaluating classification models, providing insights into model predictions. You can display total count of responses in the matrix, or if you toggle Normalize then it will be showing the ratio.
Required packages
You need below packages to use the code generated by recipe. All packages are automatically installed in MLJAR Studio.
mljar-scikit-plot>=0.3.11
Interactive recipe
You can use below interactive recipe to generate code. This recipe is available in MLJAR Studio.
In the below recipe, we assume that you have following variables available in your notebook:
- y (type Series)
- predicted (type Series)
Python code
# Python code will be hereCode explanation
Produce a plot of confusion matrix. This code can be used with binary and multi-class classification tasks.
Scikit-learn cookbook
Code recipes from Scikit-learn cookbook.
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