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Data Science and Predictive Analytics (UMich HS650)

Assessment: 15. Specialized Machine Learning Topics

1 Working with website data

• Download the Main SOCR Wiki Page and compare RCurl and httr
• Read and write XML for SOCR Main Page
• Scrape and ingest the SOCR Main Page information.

2 Network data and visualization

• Download 03_les miserablese_GraphData.txt
• Visualize this undirected network graph
• Summarize the graph and explain the output
• Calculate the degree and the centrality of this graph
• Find out some important nodes (corresponding to novel characters)
• Will the results change if we assume the graph is directed?

3 Data conversion and parallel computing

• Download CaseStudy12_ AdultsHeartAttack_Data.xlsx or require online
• Load this data as data frame
• Use Export() or write.xlsx() to renew the xlsx file
• Use rio package to convert this “.xlsx”" file to “.csv”
• Generate generalizing tabular data structures
• Generate a data.table
• Create disk-based data frames and perform basic calculation
• Perform basic calculation on the last 5 columns as a big matrix
• Use DIAGNOSIS, SEX, DRG, CHARGES, LOS and AGE to predict DIED with randomForest setting ntree=20000. Notice: sample without replacement to get as large as possible balanced dataset
• Run train() in caret and detect the execution time
• Detect cores and make proper number of clusters
• Rerun train() parallelized and compare the execute time
• Use foreach and doMC to design a parallelized random forest with ntree=20000 and compare the execution time against linear sequential execution.

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