Titlebook: Machine Learning and Data Mining in Pattern Recognition; 9th International Co Petra Perner Conference proceedings 2013 Springer-Verlag Berl

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Processes

SOM++: Integration of Self-Organizing Map and K-Means++ Algorithms,ering algorithm SOM++, which first uses K-Means++ method to determine the initial weight values and the starting points, and then uses Self-Organizing Map (SOM) to find the final clustering solution. The purpose of this algorithm is to provide a useful technique to improve the solution of the data c

缺乏

https://doi.org/10.1007/978-3-642-39712-7algorithms; feature selection; prediction; support vector machines; text classification; algorithm analys

灌溉

Petra PernerProceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition

頂點

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620462.jpg

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