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Regression models are statistical techniques used to understand the relationship between one or more independent variables and a dependent variable. They are widely used in various fields, including economics, biology, and machine learning, to predict outcomes and analyze trends.

There are several types of regression models, with linear regression being one of the most common. Linear regression predicts the dependent variable using a linear function of the independent variables. Other popular regression techniques include ridge regression, lasso regression, and elastic-net, which incorporate regularization to improve model performance and prevent overfitting ¹.

In regression analysis, the evaluation metric often used is R² (R-squared), which indicates how much variance in the target variable is explained by the model. Values range from 0 to 1, with higher values indicating a better fit ¹.

Overall, regression models are essential tools for data analysis, allowing researchers and practitioners to make informed decisions based on data-driven insights.

Linear Regression Models

Towards Data Science

This article discusses the basics of linear regression using Python and SciKit-Learn, including ordinary least squares, ridge, lasso, and elastic-net.

Regressions Models 101

Becoming Human: Artificial Intelligence Magazine

I heard a podcast from “Master in Business” where the host, Barry Ritholtz, and the interviewee, Howard Marks, mentioned that writing helps us illustrate what we know and we don’t know. One of my…

Regression Analysis

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Regression

Elements of Data Science

Click here to run this notebook on Colab or click here to download it . In the previous chapter we used simple regression to quantify the relationship between two variables. In this chapter we’ll get...

Basic Regression Models

Analytics Vidhya

When we talk about Machine Learning algorithms, we often think of classification problems. Indeed, the most common problems in machine learning are about classification, mainly because predicting a…

Application of various regression models

Analytics Vidhya

In this project we will cover various Regression models. For this project I have used Auto-MPG dataset from UCI machine learning repository. There are 9 attributes: 1.mpg: continuous 2. cylinders… reg...

The Three Regressions

Analytics Vidhya

When I first started my journey with Data Science and Machine Learning, I was overwhelmed by the sheer amount of information that was available on the internet. Overtime I realized that the majority…

Linear Regression

Analytics Vidhya

Regression analysis is a powerful statistical method that allows you to examine the relationship between two or more variables of interest. Regression analysis is a reliable method of identifying…

It’s all about regression — Part 1

Analytics Vidhya

In this series consisting of multiple blogs we are going to look into regression models. This is going to be different that a lot of other regression tutorials / lectures you might have seen online…

Machine Learning : Regression

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What is Regression? In statistical modelling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the ‘outcome variable’)…...

REGRESSION MODEL

Analytics Vidhya

In this article we will see how a regression model is build in Python. First, let us talk about what Regression analysis actually means.. Regression Analysis focuses on relationship between a…

Linear Regression

Dive intro Deep Learning Book

Regression problems pop up whenever we want to predict a numerical value. Common examples include predicting prices (of homes, stocks, etc.), predicting the length of stay (for patients in the hospita...