home value will be most affected by square footage, acreage, and property type a bigger house will...
TRANSCRIPT
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Predicting Real Estate Prices inPolk County, OR
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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
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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
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The Auto Numeric node was used to develop the 7 models
The RMS Error was used to shortlist the top 3 models:
RMS Error
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KNN Model
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Regression Model
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Regression - Variable Importance
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Neural Network Model
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Neural Network – Variable Importance
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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
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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
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Use the model for different counties Refinement of current model by adding
appraised values Make KNN more user-friendly
Project Extensions
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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