Classification Framework for Fraud Detection Using Hidden Markov Model
- Title
- Classification Framework for Fraud Detection Using Hidden Markov Model
- Creator
- Hegde D.S.; Samanta D.; Dutta S.
- Description
- Machine learning is described as a computer program that learns from experience E with regard to some task T and some performance measure P, if its performance on T improves with E as measured by P. Suppose we have a credit card fraud detection which watches which transactions we mark as fraud or not, and on the basis, it knows how to filter better fraudulent transactions then, E is watching your transactions is fraud or not, T is classifying your transactions as fraud or not, P is number of transactions correctly differentiated as spam or not spam. Machine learning has two types: supervised learning and unsupervised learning. Supervised learning is the type of machine learning where machine is provided with input mapped with its output, and these inputs and outputs are used to make a machine learn a particular function from the trained dataset. There are two branches of supervised learning, i.e., classification and regression. In unsupervised learning, we do not supervise model instead we allow machine to work on its own to discover information. Clustering is type of unsupervised learning. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes in Networks and Systems, Vol-291, pp. 29-36.
- Date
- 2022-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Credit card; Emission probability; Fraud detection; Hidden Markov method; Initial probability; Machine learning; Supervised learning
- Coverage
- Hegde D.S., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Dutta S., Institute of Engineering and Management, Kolkata, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981164283-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Hegde D.S.; Samanta D.; Dutta S., “Classification Framework for Fraud Detection Using Hidden Markov Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20446.