In Week 3, we started to study supervised learning and to understand supervised algorithms. 

In this assessment, you will apply supervised machine learning methods to classify Twitter spam using the provided dataset. Table 1 shows the features description of the dataset.

Assessment Requirements and Instructions

Twitter spam detection using R caret package

Follow instructions, complete all the tasks and organize answers into a word document. R script, R screenshot, your results and explanations should be covered for each question.

Here are your tasks:

Load dataset into R Studio and randomly split the dataset into training data and testing data with the ratio of 9:1.

Use training data to train a machine learning model with the knn algorithm.

Use testing data to test and evaluate the model trained in step 2 and print the confusion matrix. 

Twitter spam