Welcome to this project-based course Decision Tree Classifier for Beginners in R. This is a hands-on project that introduces beginners to the world of statistical modeling. In this project, you will learn how to build decision tree models using the tree and rpart libraries in R. We will start this hands-on project by importing the Sonar data into R and exploring the dataset.
Recommended experience
What you'll learn
Understand the concept of the decision tree algorithm
Build decision tree models
Evaluate the performance of the model
Skills you'll practice
Details to know
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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:
Getting Started
Import Required Packages
Import and Explore Dataset
Create Train and Test Sets
Train the decision tree model
Evaluating Model Performance
Wrap up
Recommended experience
Familiarity with writing R syntaxes
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Instructor
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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.