Classification Evaluation Metrics of Sklearn: AUC-ROC, Confusion Metrix and Classification Report

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In this video, we you will learn how a trained classification model is evaluated. First, you will see some very basics textual evaluation of model. Then, you will learn to code and evaluate classification model using AUC-ROC, Confusion Metrix and Classification Report of Sklearn library of Python.

In this video, we have evaluated the classification model that was trained in the previous video listed below:
1: An Experiment on MNIST Dataset To Decide Between Regression and Classification – Python | Part 01

In this video, the workspace includes windows 10 and Anaconda with Spyder as Python editor.

AUC-ROC:

Confusion Matrix:

Classification Report:

Coderific
python
keras
upsampling
convolution
network

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