1. 1 Data Mining on New Road Prediction By Qing Liu Dec. 9, 2004

2. 2 Agenda Introduction Purpose Input Output - Data Mart Techniques Applied Result Uncompleted Learned From This Project Question?

3. 3 Introduction Caltrans’ Interagencies tracking system has seven agencies: - ACOE, Army Corps of Engineers - CCC, CA Coastal Commission - DFG, CA Department of Fish and Game - EPA, Environmental Protection Agency - FWS, Fish and Wildlife service - NOAA, National Oceanic & Atmospheric Administration - OHP, Office of Historic Preservation

4. 4 Purpose Only ACOE, CCC, FWS and OHP applied for projects dealing with building new roads in the past few years. This project will predict the budget these agencies need on building road in the next three years.

5. 5 Input

6. 6 Output - Data Mart Star Schema Project Table autoID (PK) District County Route Postmile… ACOE IDNUM(FK) Office App_date Resp_date… Fact Table OHP IDNUM(FK) Office App_date Resp_date… FWS IDNUM(FK) Office App_date Resp_date… CCC IDNUM(FK) Office App_date Resp_date… Dimension Table

7. 7 Techniques Applied PD_test.mdb (Data source) PD_test.xls Ohp.xlsccc.xlsFws.xlsProject.xlsAcoe.xls Agencies.csv WEKA Transformation1 Transformation2 Transport and convert Load District.csv (636 cases) (428 cases)

8. 8 Access query - cleaning and calculation Convert – CSV (MS-DOS) Filters – supervised  attribute  ClassOrder Classifier – LinearRegression & J48 Techniques Applied (continue)

9. 9 Result

10. 10 Result (continue)

11. 11 Result (continue)

12. 12 Uncompleted Get the cost per mileage information Add new field “predict_cost” Run through WEKA and get the final result

13. 13 Learned From This Project Apply data mining technique to real database How to find the right algorithm and model The power of data mining in prediction How to use WEKA

14. 14 Reference http://prdownloads.sourceforge.net/weka/weka.ppt Concepts and Techniques" by Jiawei Han and Micheline Kamber, Morgan Kaufmann 2001. Concepts and Techniques" by Jiawei Han and Micheline Kamber, Morgan Kaufmann 2001. “Data Mining – Practical Machine Learning Tools and Techniques with Java Implementations” by Ian H. Witten and Eibe Frank, Morgan Kaufmann 2000. “Data Mining – Practical Machine Learning Tools and Techniques with Java Implementations”

15. 15 Question ?