Description
Concepts and techniques of data mining. Methods for data summarization and data preprocessing. Algorithms for finding frequent patterns and association analysis; classification; cluster analysis and anomaly detection. Model selection, model evaluation and statistical significance testing. Applications of data mining and coping with Big Data.
Reference text in its original language
Concepts and techniques of data mining. Methods for data summarization and data preprocessing. Algorithms for finding frequent patterns and association analysis; classification; cluster analysis and anomaly detection. Model selection, model evaluation and statistical significance testing. Applications of data mining and coping with Big Data.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/grad/courses/COMP/