Data clustering algorithms Source: Wikipedia. Pages: 90. Chapters: BIRCH (data clustering), Canopy clustering algorithm, Cluster-weighted modeling, Cobweb (clustering), Complete-linkage clustering, Constrained clustering, CURE data clustering algorithm, Data stream clustering, DBSCAN, Expectation?maximization algorithm, FLAME clustering, Fuzzy clustering, Hierarchical clustering, Information bottleneck method, K-means++, K-means clustering, K-medians clustering, K-medoids, Linde?BuzöGray algorithm, Lloyd's algorithm, Nearest-neighbor chain algorithm, Neighbor joining, OPTICS algorithm, Pitman?Yor process, Self-organizing map, Single-linkage clustering, Spectral clustering, SUBCLU, UPGMA, Ward's method. Excerpt: 208 article summaries including: An Efficient Constrained K-Means Clustering using Self Organizing Map . Classification of Indian power coals using K-means clustering and self organizing map neural network . 4 The Kernel Pitman-Yor Process . The Expectation Maximization Algorithm . Space-Alternating Generalized Expectation-Maximization Algorithm . Expectation-maximization algorithm with local adaptivity . Distributed Data Clustering Using Expectation Maximization Algorithm . Symbol Based Modulation Classification using Combination of Fuzzy Clustering and Hierarchical Clustering . 12 The information bottleneck method . Rough self organizing map . Associative Self-Organizing Map . Supervised k-Means Clustering . A Parallel Training Algorithm for Hierarchical Pitman-Yor Process Language Models . 22 Parameter Estimation from Censored Samples using the Expectation-Maximization Algorithm . On-line expectation-maximization algorithm for latent data models . Comparing Approaches to Initializing the Expectation-Maximization Algorithm . On-line gossip-based distributed expectation maximization algorithm . A maximum likelihood expectation maximization algorithm with thresholding . A multiresolution diffused expectation-maximization algorithm for medical image segmentat [...] Autor: Source: Wikipedia Wydawnictwo: Books LLC, Reference Series Rok wydania: 2013 Okładka: miękka Liczba stron: 90 Wymiary: 24.6 x 18.9 x 0.8 cm Język: angielski ISBN: 9781155917122