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Description: 这是一个对于L2范数下的Earth Mover Distance的VC实现。
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Size: 11711 |
Author: B X |
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Description: 这是一个对于L2范数下的Earth Mover Distance的VC实现。-This is an L2 norm for the Earth Mover Distance realize the VC.
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Size: 11264 |
Author: B X |
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Description: C++ and Matlab work togather to compute the distance between to sets of vectors or matrix (chi-suare, X2, L2 and etc.)
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Size: 29696 |
Author: mason |
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Description: 独立主成分分析与主成分分析代码，速度比较快，而且比较好用-In these first experiments, both ICA and whitened PCA are used to compress the data, and all the components are used for classifying the examples. The classifier used is a 1-NN with Euclidean distance. The results shown in next sections are clear: when a rotational invariant classifier is used (as 1-NN with L2-norm) the classification results of FastICA/whitened PCA are equivalent, while the difference between Infomax and whitened data es significant but small
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Size: 69632 |
Author: 李阳 |
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Description: image retrieval using L2 distance:euclidien distance between 2 histograms
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Size: 872448 |
Author: amoula |
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Description: 构造一个具有n个外部节点的扩充二叉树，每个外部节点Ki有一个Wi对应，作为该外部节点的权。使得这个扩充二叉树的叶节点带权外部路径长度总和最小： Min( W1 * L1 + W2 * L2 + W3 * L3 + … + Wn * Ln)
Wi:每个节点的权值。
Li:根节点到第i个外部叶子节点的距离。
编程计算最小外部路径长度总和。-Constructing a binary tree with n external expansion nodes, each external node has a Ki Wi corresponds, as the weight of the external node. This extension allows the leaf node of a binary tree with the sum of the minimum length path right outside: Min (W1* L1+ W2* L2+ W3* L3+ ...+ Wn* Ln) Wi: weight for each node. Li: distance the root node to the i-th external leaf nodes. Programming calculate the sum of the minimum external path length.
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Size: 1024 |
Author: nature |
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Description: Fuzzy c-means clustering (FCM) with spatial constraints (FCM_S) is an
effective algorithm suitable for image segmentation. Its effectiveness contributes not
only to introduction of fuzziness for belongingness of each pixel but also to
exploitation of spatial contextual information. Although the contextual information
can raise its insensitivity to noise to some extent, FCM_S (1) still lacks enough
robustness to noise and outliers and (2) is not suitable for revealing non-Euclidean
structure of the input data due to the use of Euclidean distance (L2 norm).
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Size: 36864 |
Author: mahsy |
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Description: In mathematics, the Euclidean distance or Euclidean metric is the ordinary (i.e. straight-line) distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm. Older literature refers to the metric as Pythagorean metric. A generalized term for the Euclidean norm is the L2 norm or L2 distance.-In mathematics, the Euclidean distance or Euclidean metric is the ordinary (i.e. straight-line) distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm. Older literature refers to the metric as Pythagorean metric. A generalized term for the Euclidean norm is the L2 norm or L2 distance.
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Size: 1024 |
Author: m |
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