Chat with us, powered by LiveChat Describe how the confusion matrix is used for model evaluation. Describe the definition of accuracy, precision, recall, sensitivity, specificity, True positive rate, False positive rate. Sy - Writeedu

Describe how the confusion matrix is used for model evaluation. Describe the definition of accuracy, precision, recall, sensitivity, specificity, True positive rate, False positive rate. Sy

Describe how the confusion matrix is used for model evaluation.

Describe the definition of accuracy, precision, recall, sensitivity, specificity, True positive rate, False positive rate.

Synthesize real-life examples where you would rely on each one of these measures to evaluate prediction, or classification, performance of your model.

What is a Lift chart? Explain in what situations you would use it?

What is ROC chart? Explain in what situations you would use it?

You are encouraged to help each other in understanding Unit Activities and practicing with scripts and answering the questions in the discussion forum.

While you are watching the videos, and while you are reading the required texts, (Book chapter and articles) in “Unit 6: Activities” experiment with scripts and exercises in the Book chapter and the content and/or similar scripts. Practice with R scripts discussed in those resources using the  installed Rstudio on your computer.

Call the libraries you use within every one of your scripts (even if you have called it in your command line) because your professor should be able to run your script on his/her computer. When you use one of the functions from a library, specify the library you are using by ”::“ notation. For example:

library(ggplot2)

library(mlbench)

library(caret)

ggplot2::ggplot(…….)

caret::train(……..)

Make sure that you show what is the data-frame that is being used and how it has been loaded such that the instructor can run your script.

Add comments to your “.R”  script such that the reader would understand what you are intending by each command.

(OPTIONAL: If possible, for your working environment, then make an Rmarkdown document from your scripts with comments about what you have learned. Then Knit it to a pdf and upload three files to the Learning Activity Grade container.)

The file name should have this format: ActivityU4-firstnamelastname. For example, the file names will be:

LAU6-By-John-Smith.R          ( the necessary Script)

LAU6-By-John-Smith.Rmd    ( + if possible R Markdown document)

LAU6-By-John-Smith.pdf      (+ if possible the result of knitting your scripts in Rmarkdown document that includes the outcomes)

The place you MUST upload these files is to the  "Learning Activity 6: grade" container.

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