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Clustering and Outlier Detection

Use the BuddyMove Data Set available at UCI Reposi- tory. This data set contains information of the user interests that was extracted from user reviews published in [login to view URL] about various types of point of in- terests in South India. The data set was built considering the reviews published by 249 users that fall within 6 different categories: Sports, Religious, Nature, Theatre, Shopping and Picnic. The number of reviews in each category for each user is captured. More details about this data set can be found on the UCI webpage https://archive.ics.uci.edu/ml/datasets/BuddyMove+Data+Set

The data set is available for download

Your solution should be an R Notebook. You should explain and justify all the choices that you made.


Consider the BuddyMove Data Set. Load the data set into R and remove the first column containing the [login to view URL] information.

a. Compare and evaluate 4 clustering solutions on this data set. Present the solution that you consider to be the most suitable for this task and justify.

b. Apply different outlier detection methods on the data set. Discuss your results.

Kĩ năng: Khai thác dữ liệu, Ngôn ngữ lập trình R, Web Scraping, Xử lí dữ liệu, Khoa học dữ liệu

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( 1 Nhận xét ) Halifax, Canada

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hello i can achieve this project perfectly using R I master r programming and clustring / classification using kmeans . knn and decision tree please contact me for more details best regards

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