Altima: A KBB-like Reference Pricing System
-
Upload
neil-ryan -
Category
Data & Analytics
-
view
779 -
download
0
Transcript of Altima: A KBB-like Reference Pricing System
![Page 1: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/1.jpg)
A KBB-like Reference Pricing System ---- Using Machine Learning
Team: Altima Hao Zhu Yingqi Yang
![Page 2: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/2.jpg)
Product
A KBB-like Reference Pricing System
The end product could be integrated with online apt./room/house etc. rental listings to provide people looking for rental housing with a reference point for rent negotiation
Rental Details Asking Rent Reference Price % Above Reference
…… 1000 800 25%
![Page 3: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/3.jpg)
Business Model
• Build our own service by scraping online rental listings and applying this system
• Cooperate with online rental listing providers such as Craigslist and provide this system as a value-added service
• Promote this system to other similar web services such as ebay auction to predict closing price
![Page 4: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/4.jpg)
Approach
Data Set
Source Seattle Apt/House Rent Price Downloaded from GitHub
Size• Total of 2313 Entries from Nov. 2014• Training/Validation: 75/25
Attribute
• Responds (Price) • 14 Predictors
(Number of Bedrooms, Room Size, Listing Title……)
![Page 5: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/5.jpg)
Approach
Data Exploration
Outlier:
Price < 600 or Price > 3100
Rent Price Distribution
Rent Price Histogram
![Page 6: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/6.jpg)
Approach
Text Mining on Listing Title Variable
![Page 7: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/7.jpg)
Approach
Model Selection
(1) K Nearest Neighbors – Regression Model (KNN)
An algorithm that stores all available cases and predict the numerical target based on a similarity measure (e.g., distance functions).
Numeric Variables -- Euclidean Categorical Variables – Hamming Distance
![Page 8: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/8.jpg)
Approach
Model Selection
(1) K Nearest Neighbors – Regression Model (KNN)
Size Beds Zip code Price1 1710 4 98115 25002 2200 2 98199 28953 1420 2 98117 2150
Step1: Standardize Data Set
Size Beds 98104 98115 98117 Price1 0.564 0.212 0 1 0 25002 0.731 0.091 1 0 0 28953 0.465 0.091 0 0 1 2150
![Page 9: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/9.jpg)
Approach
Model Selection
(1) K Nearest Neighbors – Regression Model (KNN)Step2: Give Reasonable Weights
Variable Size Bath Bed Zip Code ……
Weight 5 4 3 2 ……
![Page 10: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/10.jpg)
Approach
Model Selection
(1) K Nearest Neighbors – Regression Model (KNN)
Forecast 2.053 0.273 98104 ?
③①
②
Step3: Calculate Distance
K =1 Price = 2150K =2 Price = (2150+2500) /2
Size Beds 98104 98115 98117 Price Distance1 2.819 0.636 0 1 0 2500 0.82 3.654 0.273 0 0 0 2895 1.63 2.325 0.273 0 0 1 2150 0.3
![Page 11: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/11.jpg)
Approach
Model Selection
(1) K Nearest Neighbors – Regression Model (KNN)
(2) Other Models
• Decision Tree Model• Forest Model• Spline Model• Support Vector Machine Model (SVM)
![Page 12: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/12.jpg)
Approach
Model Comparison
Model Name MAPE RMSEKNN Regression
Model 0.17963 20.53814
Decision Tree Model 0.15522 334.49524
Forest Model 0.12895 287.84426
Spline Model 0.16774 408.67882
* SVM Model 0.15726 336.83526
* Not able to implement in Alteryx Designer; Used R to develop instead
Result: Ensemble Model
![Page 13: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/13.jpg)
Demo
Baths Beds Size Zip Code Price Reference Price % Above Reference
1 1 828 98121 2,055 2,038 0.011 2 900 98117 1,800 1,700 0.061 1 583 98121 2,395 1,395 0.721 1 577 98121 1,398 1,595 -0.12
![Page 14: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/14.jpg)
Model Improvement
• Use a larger dataset to build the model to make it stronger
• Add attributes such as availability of pool, security guard, etc.• Include contents of the listings for text mining• Distinguish between house and apartment
• Add time component to the model to handle trend and seasonality in rent price
• Do more research on the variables to get better weights for KNN Regression Model
![Page 15: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/15.jpg)
Q & A
![Page 16: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/16.jpg)
AppendixK Nearest Neighbors – Regression Model (KNN)
D1 ¿ 2√(2.053−2 .819)2+(0.273−0.636)2+1
D2 ¿ 2√(2.053−3 .654 )2+(0.273−0.273)2+0
F_Price = 2150
F_Price = (2150+2500) / 2
K = 1
K = 2
Step3: Calculate Distance
Forecast 2.053 0.273 98104 ?
③①
②Size Beds 98104 98115 98117 Price Distance
1 2.819 0.636 0 1 0 2500 0.82 3.654 0.273 1 0 0 2895 1.63 2.325 0.273 0 0 1 2150 0.3
![Page 17: Altima: A KBB-like Reference Pricing System](https://reader035.fdocuments.net/reader035/viewer/2022062503/58e4a2001a28abf5428b648d/html5/thumbnails/17.jpg)
Reference
http://www.ncbi.nlm.nih.gov/pubmed/16723004
http://www.cs.upc.edu/~bejar/apren/docum/trans/03d-algind-knn-eng.pdf