Machine Learning: Predict Poisonous Mushrooms using a Random Forest Model and the FFTrees Package in 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 exploration using R and ggplot2.

Apply a Random Forest model using the FFTrees package in R.

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 using the FFTrees package in R, and examine the results using 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

R ProgrammingRandom Forest Model

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 FFTrees package developed by Nathaniel Phillips. There will be a short discussion about the Interface and an Instructor Bio.

  2. Task 2: The Learners will get practice doing Exploratory Analysis 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 in R. The Instructor will show the Learner how to do it using the Base R way and also using a function from the caret package.

  4. Task 4: The Learner will get experience with the syntax of FFTrees package and then will execute the Random Forest Model.

  5. Task 5: The Learner will get practice with building a Confusion Matrix to evaluate model performance.

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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