English, asked by hharjot14, 6 months ago

a. Much confusion
predicted
O
Di.is
ii. are
Ο Ο Ο
iii. were
iv. will​

Answers

Answered by snehalgunjalkar767
0

Answer:

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Explanation:

Confusion Matrix – Not So Confusing!

Have you been in a situation where you expected your machine learning model to perform really well but it sputtered out a poor accuracy? You’ve done all the hard work – so where did the classification model go wrong? How can you correct this?

There are plenty of ways to gauge the performance of your classification model but none have stood the test of time like the confusion matrix. It helps us evaluate how our model performed, where it went wrong and offers us guidance to correct our path.

confusion_matrix

In this article, we will explore how a Confusion matrix gives a holistic view of the performance of your model. And unlike its name, you will realize that a Confusion matrix is a pretty simple yet powerful concept. So let’s unravel the mystery around the confusion matrix!

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Here’s what we’ll cover:

What is a Confusion Matrix?

True Positive

True Negative

False Positive – Type 1 Error

False Negative – Type 2 Error

Why need a Confusion matrix?

Precision vs Recall

F1-score

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