Logistic Regression for Machine Learning

Logistic Regression is one of the most used Machine learning algorithms among industries and academia. It is a supervised learning algorithm used for classification where the target variable should be categorical. Why not Linear Regression for classification There are mainly two reasons for not fitting a linear regression on classification tasks: When we fit a…

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Difference between Logistic Regression and Support Vector Machine?

When working on classification tasks, it is important to comprehend the disparities between logistic regression and support vector machine (SVM), two prevalent machine learning techniques with distinct approaches and advantages. In this discourse, we will delve into the contrast between these two algorithms. Logistic Regression Logistic regression is a statistical method employed to model the…

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Difference between Linear Regression and Logistic Regression?

Linear regression and logistic regression are two of the most commonly used statistical techniques in machine learning and data analysis. Although both methods are used to predict outcomes, they differ fundamentally in their implementation and assumptions. In this article, we discuss the differences between linear and logistic regression. What is regression? Regression analysis is a…

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Important Supervised and Unsupervised Algorithms for Machine Learning

Machine learning is a branch of computer science and artificial intelligence that allows machines to learn automatically without special programming. It involves using algorithms and statistical models to analyze and interpret data and make predictions based on that analysis. Machine learning can be broadly divided into two types of algorithms: supervised and unsupervised. In this…

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