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R编程代写 编程作业代写 数据分析代写 统计R作业代写

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Course: STAT2604 Introduction to R Programming and Elementary Data Analysis

R编程代写 Please pack your Rmd source code file together with the output html file as one compressed file, and submit only that compressed file onto Moodle.

Total marks: 100

Please pack your Rmd source code file together with the output html file as one compressed file, and submit only that compressed file onto Moodle. Name the compressed file in the format (Name)_(UID)_A3.

Question 1. R编程代写

Download the UCI machine learning data set file ionosphere.data through: “https://archive.ics.uci.edu/ml/datasets/Ionosphere”. The goal is to predict high-energy structures in the atmosphere from antenna data. More information can be found in the data description file ionosphere.names from the website above. (Hint: data cleaning might be needed before model constrution)

a) Load the data into R, split 80% of the data samples into training set, and 20% into testing set. (20 marks) R编程代写

b) Run the following algorithms using the caret package: logistic regressions, KNN, SVM, naïve bayes, decision trees, random forest and glmnet models. Tune the each of the above models (if it does have tunning parameters) using cross-validation, and set metric=”ROC”, tuneLength=10. Compute the area under ROC curve on the testing set for each model. (50 marks)

c) Perform model selection using the function caret::resamples, visualize the result, and choose the best model for this data set. (30 marks)

The prev:

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