Dissertation/Thesis Abstract

Predicting the Market Value of Single-Family Residential Real Estate
by Lowrance, Roy E., Ph.D., New York University, 2015, 120; 3685886
Abstract (Summary)

This work develops the best linear model of residential real estate prices for 2003 through 2009 in Los Angeles County. It differs from other studies comparing models for predicting house prices by covering a larger geographic area than most, more houses than most, a longer time period than most, and the time period both before and after the real estate price boom in the United States. In addition, it open sources all of the software. We test designs for linear models to determine the best form for the model as well as the training period, features, and regularizer that produce the lowest errors. We compare the best of our linear models to random forests and point to directions for further research.

Indexing (document details)
Advisor: LeCun, Yann, Shasha, Dennis
Commitee: Caplin, Andrew, Kedeem, Zvi, LeCun, Yann, Provost, Foster, Shasha, Dennis
School: New York University
Department: Computer Science
School Location: United States -- New York
Source: DAI-B 76/08(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Computer science
Keywords: Housing prices, Los Angeles County, Market value, Real estate
Publication Number: 3685886
ISBN: 9781321624304
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