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Fraud Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
12
보존된 평가 기록
45

Fraud Detection is a vital topic that applies to many industries including the financial sectors, banking, government agencies, insurance, and law enforcement, and more. Fraud endeavors have detected a radical rise in current years, creating this topic more critical than ever. Despite struggles on the part of the troubled organizations, hundreds of millions of dollars are wasted to fraud each year. Because nearly a few samples confirm fraud in a vast community, locating these can be complex. Data mining and statistics help to predict and immediately distinguish fraud and take immediate action to minimize costs.

Source: Applying support vector data description for fraud detection

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

BAF – Base

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 12건

Yelp-Fraud

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 10건

Amazon-Fraud

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 6건

Elliptic Dataset

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 6건

BAF – Variant I

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

BAF – Variant II

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

BAF – Variant III

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

BAF – Variant IV

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

BAF – Variant V

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

FDCompCN

원본 태스크: Active Speaker Detection / Fraud Detection

평가 기록 1건

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