東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Using data mining to detect anomalou...

Olson, Stacey Ann.

FindBook

Google Book

Amazon

博客來

Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program./
作者:	Olson, Stacey Ann.
面頁冊數:	91 p.
附註:	Source: Masters Abstracts International, Volume: 41-02, page: 0405.
Contained By:	Masters Abstracts International41-02.
標題:	Economics, Agricultural. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1410647
ISBN:	0493826971

Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program.
Olson, Stacey Ann.

Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program. - 91 p.

Source: Masters Abstracts International, Volume: 41-02, page: 0405.

Thesis (M.S.)--Tarleton State University, 2002.

Research regarding anomalous producer and county soybean production was conducted on the United States Department of Agriculture/Risk Management Agency Book of Business for reinsurance years 1994 to 2001. The purpose of the analysis was to assist RMA in the identification of anomalous producers and analyze the relationship between anomalous producers and anomalous counties by developing a data mining pattern detection model. Identification of producers and counties as anomalous is not <italic>prima facie</italic> evidence of fraud. However, the outlier detection of anomalous producers and anomalous counties has raised some interesting questions because both sets of outliers cluster at or near Land Resource Region boundaries.

ISBN: 0493826971Subjects--Topical Terms:

626648
Economics, Agricultural.

Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program.
LDR:01537nam 2200241 a 45 001 929557
005 20110427
008 110427s2002 eng d
020 $a 0493826971
035 $a (UnM)AAI1410647
035 $a AAI1410647
040 $a UnM $c UnM
100 1 $a Olson, Stacey Ann. $3 1253045
245 1 0 $a Using data mining to detect anomalous producer behavior: An analysis of soybean production and the federal crop insurance program.
300 $a 91 p.
500 $a Source: Masters Abstracts International, Volume: 41-02, page: 0405.
502 $a Thesis (M.S.)--Tarleton State University, 2002.
520 $a Research regarding anomalous producer and county soybean production was conducted on the United States Department of Agriculture/Risk Management Agency Book of Business for reinsurance years 1994 to 2001. The purpose of the analysis was to assist RMA in the identification of anomalous producers and analyze the relationship between anomalous producers and anomalous counties by developing a data mining pattern detection model. Identification of producers and counties as anomalous is not <italic>prima facie</italic> evidence of fraud. However, the outlier detection of anomalous producers and anomalous counties has raised some interesting questions because both sets of outliers cluster at or near Land Resource Region boundaries.
590 $a School code: 1081.
650 4 $a Economics, Agricultural. $3 626648
690 $a 0503
710 2 0 $a Tarleton State University. $3 1253046
773 0 $t Masters Abstracts International $g 41-02.
790 $a 1081
791 $a M.S.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1410647