Improved Niching and Encoding Strategies for Clustering Noisy Data Sets

Clustering is crucial to many applications in pattern recognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most suffer from several shortcomings. We formulate requirements for efficient encoding, resistance to noise, and ability to discover the number of clusters automatically.

• Type: Conference
• Year: 2004
• Where: GECCO
• Authors: Olfa Nasraoui, Elizabeth Leon
• Keywords: Data Mining, Evolutionary Techniques, GECCO 2004, Pattern Recognition