Learn to use the “Data Mining with R” (DMwR) package and R software to build and evaluate predictive data mining models.

What you’ll learn

Understand how to implement and evaluate a variety of predictive data mining models in three different domains, each described as extended case studies: (1) harmful plant growth; (2) fraudulent transaction detection; and (3) stock market index changes.

Perform sophisticated data mining analyses using the “Data Mining with R” (DMwR) package and R software.

Have a greatly expanded understanding of the use of R software as a comprehensive data mining tool and platform.

Understand how to implement and evaluate supervised, semi-supervised, and unsupervised learning algorithms.

Requirements

Students will need to install no-cost R software and the no-cost RStudio IDE (instructions are provided).

Description

Case Studies in Data Mining was originally taught as three separate online data mining courses. We examine three case studies which together present a broad-based tour of the basic and extended tasks of data mining in three different domains: (1) predicting algae blooms; (2) detecting fraudulent sales transactions; and (3) predicting stock market returns. The cumulative “hands-on” 3-course fifteen sessions showcase the use of Luis Torgo’s amazingly useful “Data Mining with R” (DMwR) package and R software. Everything that you see on-screen is included with the course: all of the R scripts; all of the data files and R objects used and/or referenced; as well as all of the R packages’ documentation. You can be new to R software and/or to data mining and be successful in completing the course. The first case study, Predicting Algae Blooms, provides instruction regarding the many useful, unique data mining functions contained in the R software ‘DMwR’ package. For the algae blooms prediction case, we specifically look at the tasks of data pre-processing, exploratory data analysis, and predictive model construction. For individuals completely new to R, the first two sessions of the algae blooms case (almost 4 hours of video and materials) provide an accelerated introduction to the use of R and RStudio and to basic techniques for inputting and outputting data and text.

Case_Studies_in_Data_Mining_with_R.7z.001

Case_Studies_in_Data_Mining_with_R.7z.002

Case_Studies_in_Data_Mining_with_R.7z.003

Case_Studies_in_Data_Mining_with_R.7z.004

Case_Studies_in_Data_Mining_with_R.7z.005

Case_Studies_in_Data_Mining_with_R.7z.006

Case_Studies_in_Data_Mining_with_R.7z.007

Case_Studies_in_Data_Mining_with_R.7z.008

Case_Studies_in_Data_Mining_with_R.7z.009

Case_Studies_in_Data_Mining_with_R.7z.010

Case_Studies_in_Data_Mining_with_R.7z.011

Case_Studies_in_Data_Mining_with_R.7z.012

Case_Studies_in_Data_Mining_with_R.7z.013

Case_Studies_in_Data_Mining_with_R.7z.014

Case_Studies_in_Data_Mining_with_R.7z.015

Case_Studies_in_Data_Mining_with_R.7z.016