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

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En este proyecto guiado, tú:

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
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

R ProgrammingRandom Forest Model

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Instructor

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