Course Details
Subject {L-T-P / C} : CS6374 : Data Mining Laboratory { 0-0-3 / 2}
Subject Nature : Practical
Coordinator : Prof. Pankaj Kumar Sa
Syllabus
Overview of R, R data types and objects, reading and writing data, Control structures, functions, scoping rules, dates and times, Loop, functions, debugging tools Simulation, code profiling.
Implement well-known algorithms in Data Mining using R, Explore Data Mining tools like WEKA, MATLAB. Mini Project on Data Analysis using data mining tools.
Course Objectives
- To make the students understand the different constructs of R programming Languages .
- To learn various data mining techniques and their applications.
Course Outcomes
• Aware of different statistical techniques used for analyzing data. <br />Aware of various data mining algorithms for analyzing various data in numerous applications.
Essential Reading
- Pang-Ning Tan, Vipin Kumar and Michael Steinbach, Introduction to data mining, Pearson , 2007 Edition.
- Norman Matloff, The Art of R Programming: A Tour of Statistical . Software Design, - , 1st Edition
Supplementary Reading
- , ,
- , ,