Sigmoid function in logistic regression
- how logistic regression works in machine learning
- what is logistic regression and how does it work
- how does linear regression work in machine learning
- is logistic regression machine learning
Logistic regression formula explained!
Logistic regression sklearn
Logistic Regression in Machine Learning
In our previous discussion, we explored the fundamentals of machine learning and walked through a hands-on implementation of Linear Regression.
Now, let’s take a step forward and dive into one of the first and most widely used classification algorithms — Logistic Regression
What is Logistic Regression?
Logistic regression is a supervised machine learning algorithm used for classification tasks where the goal is to predict the probability that an instance belongs to a given class or not.
Logistic regression is a statistical algorithm which analyze the relationship between two data factors. The article explores the fundamentals of logistic regression, it’s types and implementations.
Logistic regression is used for binary classification where we use sigmoid function, that takes input as independent variables and produces a probability value between 0 and 1.
For example, we have two classes Class 0 and Class 1 if the value of the logistic function for an input is greater than 0.5 (threshold value) then it b
- how does logistic regression work in machine learning
- how logistic regression works