Posted on Jun 25 "Torture the data, and it will confess to anything.” – Ronald CoaseIn the vast field of machine learning, Regression models play a vital role in understanding and predicting continuous outcomes. Regression is a supervised learning algorithm. It establishes the relationship between a dependent (target) variable and one or several independent variables. It is widely used in finance, marketing, healthcare, etc. Usage of regression models varies according to the nature of data involved. In this article, we will explore the concept of regression machine learning models, their applications, and popular algorithms used for regression tasks.Regression analysis is a predictive modelling technique to model the relationship between a dependent (target) and independent (predictor) variables with one or more independent variable. It helps us understand how the dependent variable changes corresponding to the independent variables. For example, predicting checking the number of ice creams sold(target) by using the temperature (independent variable).The primary goal of regression models is to find a mathematical function that best fits the observed data points, allowing us to predict the value of the dependent variable. In Regression, the predicted output values are real numbers. It deals with problems such as predicting the price of a house or the trend in the stock price at a given time, etc.Linear RegressionThis regression technique finds out a linear relationship between a dependent variable and the other given independent variables. The below-given equation is used to denote the linear regression model:y=mx+c+ewhere m is the slope of the line, c is an intercept, and e represents the error in the model.We start by splitting the dataset into train and testwe then fit the model to trainPredictEvaluateHere's, an example notebookIn this notebook, we'll focus on regression, using an example based on a real study in which data for a bicycle sharing scheme was collected and used to predict the number of rentals based on seasonality and weather conditions. We'll use a simplified version of the dataset from that studyTemplates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Memgraph - Mar 31 Tawan Thanamatee - Apr 4 Phylis Jepchumba - May 3 Vincent A. Cicirello - Mar 30 Once suspended, mugendii_ will not be able to comment or publish posts until their suspension is removed. Once unsuspended, mugendii_ will be able to comment and publish posts again. Once unpublished, all posts by mugendii_ will become hidden and only accessible to themselves. If mugendii_ is not suspended, they can still re-publish their posts from their dashboard. Note: Once unpublished, this post will become invisible to the public and only accessible to Mugi Mugendi. They can still re-publish the post if they are not suspended. Thanks for keeping DEV Community safe. Here is what you can do to flag mugendii_: mugendii_ consistently posts content that violates DEV Community's code of conduct because it is harassing, offensive or spammy. Unflagging mugendii_ will restore default visibility to their posts. DEV Community — A constructive and inclusive social network for software developers. With you every step of your journey. Built on Forem — the open source software that powers DEV and other inclusive communities.Made with love and Ruby on Rails. DEV Community © 2016 - 2023. We're a place where coders share, stay up-to-date and grow their careers.