predicting sales price of a house
TRANSCRIPT
KaggleSomeshwar Rao Sattiraju
Predicting House Sales Prices Based On Various Factors
Various factors affect the Sale Price of houses , in this problem we are tasked to predict the Sales Price of a house based on various factors or attributes.
The Data Set is a large data set with 79 explanatory variables describing almost every aspect of residential homes in Iowa .
Problem Scenario
Correlation Matrix
Correlation of 24 Predictor variables (various factors of a house ) with Dependent variable ( House Sale’s Price )
Plotted correlation with condition (correlation greater than .325 or less then -.325)
These 24 variables satisfy the above condition and are chosen variables
<<<<<-Performing Data Wrangling
This code takes in data set from .csv file & reads all the data Dimentions: ( 1460 * 71)This code then converts categorical data into numeric
Continuation ->>>>>
Post conversion the converted data is written into a separate file.NA or corrupt values are removed & correlation of all predictor variables against dependent variable ( Sales Price ) needs to be produced
Results
The R Square value for the model to predict the House Sale’s Price is:
80.02%F-Statistics value is 183.4 , which
is high and much significant
Sale's Price Of The House = -338801.122 + 44.641*(LotFrontage) + 14350*(OverallQual) + 147.29*(YearBuilt) + 204.426*(YearRemodAdd) + 24.821*(MasVnrArea) -8423.37*(ExterQual) - 512.736*(Foundation) - 8343.79*(BsmtQual) + 18.21*(BsmtFinSF1) + 2.212*(TotalBsmtSF) - 1156.93*(HeatingQC) +6.539*(X1stFlrSF) + 33.956*(GrLivArea) - 1629.20*(FullBath) - 10201.50*(KitchenQual) +2387.47*(TotRmsAbvGrd) + 8123.94*(Fireplaces) - 412.45*(GarageType) - 146.46*(GarageYrBlt) - 793.66*(GarageFinish) + 13993.63*(GarageCars) + 7.60*(GarageArea) + 27.55*(WoodDeckSF)- 4.61*(OpenPorchSF)
Not Accurate, Though! , Predicted House Sales Price close to Actual Sales Price Of the House
Still Working On This Mode To Improve The Model Prediction Accuracy ………
Please Leave comments if you have some ideas on how to make the model predict closer to actual values!!