TY  - BOOK
AU  - Shahira Shaaban Azab Ahmed
AU  - Hesham Ahmed Hefny , 
AU  - Mohamed Farouk Abdelhady , 
TI  - Semi-supervised classification using natural-based computation / 
PY  - 2017///
CY  - Cairo : 
PB  - Shahira Shaaban Azab Ahmed , 
KW  - Particle Swarm Optimization
KW  - Semi-supervised classification
KW  - Swarm intelligence
N1  - Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Science; Issued also as CD
N2  - This Thesis presents a cluster-and-label model using PSO to optimize the cluster centroid. In addition, labeled data are used to label cluster and guide clustering process. In some domains, the number of clusters in semi-supervised classification is unknown as in the Automatic Knowledgebase Construction. This thesis proposes an algorithm 2ESPSO3 to detect the number of clusters in the dataset by using PSO to optimize silhouette score. Then, the detected numbers of clusters are used in exploratory semi-supervised classification tasks with an unanticipated cluster
ER  -