Analysis_On_House_Sales_using_LR_and_RR

This project contains dataset of house sale prices for USA. It includes homes sold between May 2019 and May 2020. Goal to determine the market price of a house given a set of features.Analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors, and so on.

Creator : Anandan Raju

Machine Learning Models used in this Project

1. Linear Regression
2. Ridge Regression

Synopsis

1. Import Packages
2. Reading DataSet
3. Checking Null Count and DataType
4. Exploring DataSet
5. Data Preprocessing
   • 5.1 Setting X and Y variables
   • 5.2 Transform Date Column
   • 5.3 Splitting DataSet
6. Models\
   • 6.1 Linear Regression
     • 6.1.1 R2 Score & Fit Percentage
   • 6.2 Feature Scaling (LR with Normalisation)
     • 6.2.1 R2 Score & Fit Percentage
   • 6.3 Ridge Regression
     • 6.3.1 R2 Score & Fit Percentage
7. Model Comparison