Results 251 to 260 of about 2,020,230 (285)
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2017
K-Means is a very common method of unsupervised learning in data mining. It is introduced by Steinhaus in 1956. As time flies, many other enhanced methods of k-Means have been introduced and applied. One of the significant characteristic of k-Means is randomize.
Chen-Ling Tai, Chen-Shu Wang
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K-Means is a very common method of unsupervised learning in data mining. It is introduced by Steinhaus in 1956. As time flies, many other enhanced methods of k-Means have been introduced and applied. One of the significant characteristic of k-Means is randomize.
Chen-Ling Tai, Chen-Shu Wang
openaire +1 more source
An Effective and Adaptable K-means Algorithm for Big Data Cluster Analysis
Pattern Recognition, 2023Haize Hu
exaly
2018
As we learned in Chaps. 7, 8, and 9, classification could help us make predictions on new observations. However, classification requires (human supervised) predefined label classes. What if we are in the early phases of a study and/or don’t have the required resources to manually define, derive, or generate these class labels?
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As we learned in Chaps. 7, 8, and 9, classification could help us make predictions on new observations. However, classification requires (human supervised) predefined label classes. What if we are in the early phases of a study and/or don’t have the required resources to manually define, derive, or generate these class labels?
openaire +1 more source
A Unified Form of Fuzzy C-Means and K-Means algorithms and its Partitional Implementation
Knowledge-Based Systems, 2021Radu-Emil Precup +2 more
exaly
The k-means Algorithm: A Comprehensive Survey and Performance Evaluation
Electronics (Switzerland), 2020Mohiuddin Ahmed +2 more
exaly
Robustness Properties of k Means and Trimmed k Means
Journal of the American Statistical Association, 1999Luis Angel Garcia-Escudero +1 more
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The global k-means clustering algorithm
Pattern Recognition, 2003Aristidis Likas, Nikos Vlassis
exaly