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Fraud Analytics: Case study using Logistic Regression

Course Summary

The application of analytics for Fraud Detection with a case study using Logistic Regression with the language of SAS.


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    Course Syllabus

    • Introduction to Fraud Analytics
      • Welcome note
      • Introduction and Problem Definition
    • Data Exploration
      • Understanding the Data
      • Treating Categorical Variables
    • Data Preparation, Model Creation and Validation
      • Data Preparation- Sampling and Missing Value Treatment
      • Data Preparation- Outlier Treatment
      • Data Partitioning
      • Variable Reduction
      • Creating Deciles
      • Variable Transformation- Part 1
      • Variable Transformation- Part 2
      • Model Creation
      • Gains Chart
      • Validation
      • Extra


Course Fee:
USD 49

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Development & Implementations and Data & Information Management Community

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