in Data Handling by

What is the difference between a Perceptron and Logistic Regression in Digital learning?

1 Answer

0 votes

A Multi-Layer Perceptron (MLP) is one of the most basic neural networks that we use for classification. For a binary classification problem, we know that the output can be either 0 or 1. This is just like our simple logistic regression, where we use a logit function to generate a probability between 0 and 1.

So, what’s the difference between the two?

Simply put, it is just the difference in the threshold function! When we restrict the logistic regression model to give us either exactly 1 or exactly 0, we get a Perceptron model:

deep learning interview questions beginners

Click here to read more about Loan/Mortgage
Click here to read more about Insurance

Related questions

+1 vote
asked Jul 17, 2020 in Other by RShastri
0 votes
asked Feb 26, 2020 in R Language by rahuljain1
0 votes
asked Jan 18, 2020 in Machine Learning by sharadyadav1986
0 votes
asked Jan 2, 2020 in Data Science by sharadyadav1986
0 votes
asked Jun 4, 2020 in Data Handling by SakshiSharma