Welcome to Predicting Credit Card Fraud with R. In this project-based course, you will learn how to use R to identify fraudulent credit card transactions with a variety of classification methods and use R to generate synthetic samples to address the common problem of classification bias for highly imbalanced datasets—the class of interest (fraud) represents less than 1% of the observations.
Predicting Credit Card Fraud with R
Taught in English
Instructor: John Garcia
Included with
Guided Project
Recommended experience
(31 reviews)
What you'll learn
Use R to identify fraudulent credit card transactions with a variety of classification methods.
Create, train, and evaluate decision tree, naïve Bayes, and Linear discriminant analysis classification models using R
Generate synthetic samples to improve the performance of your models.
Skills you'll practice
Details to know
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Guided Project
Recommended experience
(31 reviews)
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Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Task 1: Explore why imbalanced datasets are problematic for classification algorithms.
Task 2: Use R to explore a dataset.
Task 3: Create random testing and training datasets using the caret package in R.
Task 4: Use R to synthetically balance your training dataset using three techniques from the smotefamily package.
Task 5: Train three classification algorithms (decision tree, naïve Bayes, and linear discriminant analysis) using the natively imbalanced dataset, and generate the predictions for the test dataset.
Task 6: Use R to visually compare your models using the recall, precision, and F measure classification accuracy metrics.
Recommended experience
Familiarity with data analysis and using R.
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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Frequently asked questions
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.