Unfolding Logistic Regression

Unfolding Logistic Regression

Unfolding Logistic Regression. Don’t get confused with the name as it says regression but Logistic Regression is a supervised learning algorithm which is used for carrying out classification tasks.

After reading this article you’ll be equipped with the following,

  1. Hypothesis Function
  2. Sigmoid Function
  3. Cost Function

Don’t get confused with the name as it says regression but Logistic Regression is a supervised learning algorithm which is used for carrying out classification tasks.

To understand classification better let’s take an example,

Let’s say A college wants to classify whether the students will get the admission or not based on there exam scores, using the historical data they have. This task can be done using logistic regression.

Let’s start with the hypothesis function used in Logistic Regression.

“Hypothesis function approximates a target function for mapping inputs to outputs.”

Hypothesis Function and Sigmoid function which is used in Logistic Regression is given below,

Image for post

1. Hypothesis Function and 2. Sigmoid Function

Graphical representation of the sigmoid function is,

mathematics supervised-learning logistic-regression machine-learning

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

What is Supervised Machine Learning

What is neuron analysis of a machine? Learn machine learning by designing Robotics algorithm. Click here for best machine learning course models with AI

Hire Machine Learning Developers in India

We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.

Linear Regression VS Logistic Regression (MACHINE LEARNING)

Linear Regression VS Logistic Regression (MACHINE LEARNING). Linear Regression and Logistic Regression are two algorithms of machine learning and these are mostly used in the data science field.

Pros and Cons of Machine Learning Language

AI, Machine learning, as its title defines, is involved as a process to make the machine operate a task automatically to know more join CETPA

Logistic Regression with Mathematics

Logistic Regression is an omnipresent and extensively used algorithm for classification. It is a classification model, very easy to use and its performance is superlative in linearly separable class.