Run Particle Clustering » History » Revision 2
Revision 1 (Anke Mulder, 05/18/2010 02:09 PM) → Revision 2/12 (Anke Mulder, 05/18/2010 02:13 PM)
h1. Run Particle Clustering After interimage variance analysis and data reduction procedures done via feature analysis, particles are ordered and summed according to their relative similarity (proximity in reduced multidimensional image point space). Traditional methods include k-means and hierarchical ascendant classification (_Frank et. (Frank et al Journal _Journal of Microscopy v150,99-115 (1988))._ Microscopy_ h2. Particle Clustering Feature Analysis Procedures # [[Hierarchical or K-means Clustering]] [[Spider Coran Classification]] # [[Xmipp Kerden Self-Organizing Map]] # [[Xmipp Rotational Kerden Self-Organizing Map]] ______ [[Run_Alignment|<Run Alignment]] | [[Run Particle Clustering|Run Particle Clustering >]] ______