Predicting Real Estate Prices inPolk County, OR

Home value will be most affected by square footage, acreage, and property type

A bigger house will be more expensive than a smaller one

A house in an area zoned for farming will be less expensive per acre than a house zoned in a residential area.

Hypothesis

Variables Used:◦ Adjusted sales price◦ Land size◦ Effective year built◦ Living area◦ Bedrooms◦ Full bathrooms◦ Half bathrooms◦ Zone◦ Stat Class (Residence Type)◦ Study Area◦ Zones

Model Development Models Tried

KNN Regression General Linear

Regression CHAID Neural Networks CART SMV

The Auto Numeric node was used to develop the 7 models

The RMS Error was used to shortlist the top 3 models:

RMS Error

KNN Model

Regression Model

Regression - Variable Importance

Neural Network Model

Neural Network – Variable Importance

Model Testing

Stat Class

SA_3.0 Living Area

Land Size

Full Bath

Bed Res. Zone

Yr. Built

House 1 131 1 1480 0.153 2 3 1 1977

House 2 143 1 3148 0.237 3 4 1 1980

Zillow.com

Regression KNN Neural Networks

House 1 $152,500 $153,015 $157,550 $162,239

House 2 $281,506 $288,429 $271,470 $231,136

2 main errors:◦ Overpriced houses

Not of major concern as house prices can be brought down by gauging market interest

◦ Underpriced houses Top 3 models underpriced houses by 5%, 36% of the

time

Errors

Use the model for different counties Refinement of current model by adding

appraised values Make KNN more user-friendly

Project Extensions

We recommend the regression model

Generally, our hypothesis was accurate◦ Variables seen as most important were square

footage and lot size◦ Certain property types were also seen as

important

Half bath was seen as an important variable Zoning was not seen as a very important

variable in indicating house prices

Conclusion