TIM-6130: Data Mining

Mahnane, L. (2017). Recommending learning activities in social networks using data mining algorithms. Educational Technology & Society, 20(4), 11-23.
Review information on how algorithms are used in the analysis of big data sets.

Ray, S. (2017, September 11). 6 easy steps to learn naive Bayes algorithm with codes in Python and R. Analytics Vidhya.
A good site explaining naive Bayes with Python and R. Read 1-6 in the table of contents; it is optional, not required to create an account to watch the video.

Li, Raymond. (2015, May). Top 10 data mining algorithms, explained. KDnuggets.
A great list of the top 10 algorithms.

Tripathy, M., & Panda, A. (2017). A study of algorithm selection in data mining using meta-learning. Journal of Engineering Science & Technology Review, 10(2), 51-64.
Review information on algorithms and data mining.

Witten, I. H., Frank, E., & Hall, M. A. (2017). Algorithms: the basic methods. Data mining: Practical machine learning tools and techniques (3rd ed.), 91-160.
Read Chapter 4: Algorithms: The Basic Methods. Review information on statistics in data mining.

Wicker, Z. T., & Browning, J. B. (2021). Health information management statistics. Visualizing health care statistics: A data-mining approach (2nd ed., pp. 152-169). Jones & Bartlett Learning.
Chapter 8 provides a great example of how to use R and the Naive Bayes algorithm for data mining on the Iris data set that is built in.