Topics include: classification, clustering, association analysis, anomaly detection.
Exams are closed book. Assignments must be performed individually. Group work is NOT allowed, unless otherwise stated by the instructor. Any deviation from this policy will be considered a violation of the
GMU Honor Code
In addition, the CS department has its own Honor Code policies. Any deviation from this is also considered an Honor Code violation.
Software and Data (will be extended, come back!):
UCI Machine Learning Repository is a repository of databases, domain theories and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms.
UCI Knowledge Discovery in Databases Archive is an online repository of large data sets which encompasses a wide variety of data types, analysis tasks, and application areas
More datasets
Resources: software and data
Weka is an open source Java package implementing many learning algorithms
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
SVM light and LibSVM are two popular implementations of various SVM algorithms