Linear Regression

Regression analysis is a form of predictive modelling technique which investigates the relationship between a dependent and independent variable.

Linear regression is a basic and commonly used type of predictive analysis which usually works on continuous data.

The main goal of Gradient descent is to minimize the cost value. i.e. min J(θo, θ1)

Choosing a perfect learning rate is a very important task as it depends on how large of a step we take downhill during each iteration.

This general equation is for?

Advantages of using Polynomial Regression are:

Disadvantages of using Polynomial Regression are:

simple linear regression is a type of regression analysis where the number of independent variables is ____ and there is a linear relationship between the independent(x) and dependent(y) variable.

Residual plot helps in analyzing the model using the values of residues. It is plotted between predicted values and residue. Their values are standardized. The distance of the point from 0 specifies how bad the prediction was for that value. If the value is positive, then the prediction is low. If the value is negative, then the prediction is high. 0 value indicates prefect prediction. Detecting residual pattern can improve the model.

Non-random pattern of the residual plot indicates that the model is,

Characteristics of a residue are: