Random Forest Regression 1. What is Random Forest Regression?¶ Random Forest Regression is an advanced machine learning method used to predict continuous values (like house prices). It combines multiple decision trees to improve accuracy and reduce errors. 2. How Random Forest Works¶ Instead of using just one decision tree (which …
Read More »Decision Tree Regression
Decision Tree Regression 1. What is Decision Tree Regression?¶ Decision Tree Regression is a method used to predict a continuous value (like house price) based on input features (like size, number of rooms). It uses a tree-like model to make decisions. 2. How Decision Trees Work¶ The model splits the …
Read More »Support Vector Regression
Support Vector Regression’ 1. What is Support Vector Regression?¶ SVR is a type of machine learning method used to predict continuous values (like prices) based on input features (like size, number of rooms). It’s based on the concept of support vectors, which help in defining the best prediction model. 2. …
Read More »Polynomial Regression
Polynomial Regression 1. What is Polynomial Regression?¶ Polynomial Regression is a type of regression analysis that models the relationship between a dependent variable (like house price) and one or more independent variables (like size) as an nth degree polynomial. It helps capture relationships that are not linear (straight lines). 2. …
Read More »Multiple Linear Regression:
Multi-linear Regression Multiple Linear Regression Explained Simply¶1. What is Multiple Linear Regression?¶ It’s a method used to predict one thing (like house price) based on multiple other factors (like size, number of bedrooms, and location). It helps us understand how different factors influence the outcome. 2. The Equation¶ The equation …
Read More »Linear Regression
Linear Regression 1. What is Linear Regression?¶ Linear regression helps us predict one thing (like house price) based on another (like house size). It finds a straight line that best fits the data. 2. The Equation of Linear Regression¶ The equation looks like this: $Y = mX + b$ Where: …
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