12/19/2023 0 Comments Hyperplan in linear regressionSimple Linear Regression defines the relationship between two different variables through a straight line equation which tries to represent the relationship between one dependent and one independent variable. Generally, regression analysis is done for prediction purposes, such that knowing the X parameters you can assume Y parameter which is significantly close to real value.īasically there are two main types of regression : This equation simply illustrates that the value of Y is dependent on the value of X and some other facts like intercept, slope, and regression residual. Here X and Y are the two variables that we are observing. X = independent variable(the variable that you are using to predict Y ) Y = dependent variable(the variable that you are trying to predict ) This straight line is represented by a simple formula which is also called regression equation: To determine the same relationship there is another method often used called regression which beliefs in building a straight line which best represents the relation between two variables. We examine correlation to identify the type of relationship our variables have in between and their strength which is represented by a numerical value between -1 to 1. On a simple data set, the relationship between two observations (variables) is called correlation. You must have heard about the concept of correlation. If not, WHAT ARE PYTHON PACKAGES FOR DATA SCIENCE? and IMPORTING AND EXPORTING DATA IN PYTHON WITH PANDA are a few articles on a short introduction to these libraries.īefore diving into simple and multiple linear regression let me give you some theoretical concept on simply “Regression”. Since you are into regression algorithms now you must have used these libraries for data analysis tasks before. In this tutorial, we will be working with pandas, numpy, sklearn libraries and some visualization libraries like matplotlib and seaborn. Hi everyone! In this post I will be giving you some insight on regression analysis and an experiment on a dataset that will make you aware about the concept of simple and multiple linear regression.
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