How to create a Confusion Matrix in Python? | Performance metrics in Machine Learning
Logistic regression is a type of regression that we can use when the response variable is binary. A familiar way to assess the quality of a logistic regression model is to create a confusion matrix.
A confusion matrix is a table that is used to evaluate the performance of a classification algorithm. It is a graphical representation of the actual and predicted classifications made by the algorithm.
In this video, you will learn about Performance metrics in Machine learning. Our expert will also explain about Confusion matrix and how to create a confusion matrix in Python using Jupyter notebook.
----------Video content--------------------------
00:00 Introduction and Agenda
01:34 What is Classification & Regression
04:20 Performance Metrics
08:11 AUC-ROC Curve
10:40 Introduction to Confusion Matrix
16:07 Create a confusion matrix in Python using Jupyter notebook
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