Main Reference PaperMultiple instance learning for credit risk assessment with transaction data, Knowledge-Based Systems, 2018.[Python]
  • #The proposed comprehensive assessment method utilizes the Radial Basis Function (RBF) Multiple Instance Learning (MIL) methods to capture the features from the historical transaction behavior. In addition, it exploits the information about the socio-demographic characteristics, dynamic transaction behavior, and the loan application information of an applicant for credit scoring.

Description
  • #The proposed comprehensive assessment method utilizes the Radial Basis Function (RBF) Multiple Instance Learning (MIL) methods to capture the features from the historical transaction behavior. In addition, it exploits the information about the socio-demographic characteristics, dynamic transaction behavior, and the loan application information of an applicant for credit scoring.

  • To analyze and scoring individual credit

Aim & Objectives
  • To analyze and scoring individual credit

  • The proposed system is improved by capturing the comprehensive features for the efficient analysis of personal transaction behavior.

Contribution
  • The proposed system is improved by capturing the comprehensive features for the efficient analysis of personal transaction behavior.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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