Публикации с тэгом "Distance"

СТАТЬЯ Support Vector Machine Classifier

Support vector machines SVMs are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n-dimensional space, an SVM will construct a separating hyperplane in that space, one which maximizes the margin between the two data sets. To calculate the margin, two parallel hyperplanes are constructed, one on each side of the separating hyperplane, which are "pushed up against" the two data sets. Intuitively, a good separation ...

СТАТЬЯ Fuzzy c-means clustering algorithm v.0.3 for Multidimensional Data

Overview The new version is adapted to the multidimensional data clustering. It means that objects can have more than two characteristics. Lets look how existing code was changed to apply for the multidimensional data clustering. ClusterCentroid class was exluded This class was an exact copy of the ClusterPoint class so I exluded it from the solution to make code more clear. CusterPoint class changes The Coords property was added for storing any number of object properties:             public Li...

СТАТЬЯ Self Organizing Map (SOM)

Self-Organizing Map Overview A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (typically two dimensional), discretized representation of the input space of the training samples, called a map. Self-organizing maps are different than other artificial neural networks in the sense that they use a neighborhood function to preserve the topological properties of the input spa...