Predict Diabetes with a Random Forest using R

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在此指导项目中,您将:

Complete a random Training and Test Set from one Data Source using an R function.

Practice data distribution using R and ggplot2.

Apply a Random Forest model.

Clock2 Hours
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this 1-hour long project-based course, you will learn how to (complete a training and test set using an R function, practice looking at data distribution using R and ggplot2, Apply a Random Forest model to the data, and examine the results using RMSE and a Confusion Matrix). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培养的技能

Random ForestComputer ProgrammingR ProgrammingModelling

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Task 1: In this task the Learner will be introduced to the Course Objectives, which is to how to execute a Random Forest Model using R and the Pima Indians data set. There will be a short discussion about the Interface and an Instructor Bio.

  2. Task 2: The Learners will get experience looking at the data using ggplot2. This is important in order for the practitioner to see the balance of the data, especially as it relates to the Response Variable.

  3. Task 3: The Learner will get experience creating Testing and Training Data Sets. There are multiple ways to do this and the Instructor will go over two of them in this Task.

  4. Task 4: The Learner will get experience with the syntax of the Caret, an R package. There will be a discussion on how you can apply hundreds of algorithms to a single problem using the same syntax using Caret as well.

  5. Task 5: The Learner will get experience evaluation models in this Task. RMSE will be discussed as well as the Confusion Matrix. The conclusion of the course will use the two evaluation metrics see how well the model performed on the test data set.

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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