Machine Learning For Regression

Linear Regression is the first step to climb the ladder of machine learning algorithm. Regression is a Machine Learning technique to predict how much of something given a set of variables.

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Regression and Classification problems are a part of.

Machine learning for regression. Linear regression is a statistical algorithm that can be used to make predictionsIts one of the most well-known and understood algorithms in statistics machine learning data science operations research or any other field that requires someone to predict unknown values from known quantities for example future stock prices based on historical price fluctuations. What is linear regression. Regression uses labeled training data to learn the relation y fx between input X and output Y.

Regression techniques mostly differ based on the number of independent variables and the type of relationship between the independent and dependent variables. 2 days agoTypes of Machine Learning. It is an ML technique where models are trained on labeled data ie output variable is provided in these types of problems.

Regression is a method of modelling a target value based on independent predictors. Here the models find the mapping function to map input variables with the output variable or the labels. Linear Regression comes under supervised learning where we have to train the Linear Regression.

This method is mostly used for forecasting and finding out cause and effect relationship between variables. The major types of regression are linear regression polynomial regression decision tree regression and random forest regression.

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