S29NS-J 128 Megabit (8 M x 16-Bit), 64 Megabit (4 M x 16-Bit), 32 Megabit (2 M x 16-Bit), and 16 Megabit (1 M x 16 Bit), 110 nm CMOS 1.8-Volt only Simultaneous Read/Write, Burst Mode Flash Memories Data Sheet
上传时间： 2014-01-01
上传用户：qoovoop
k-means是一种经典的聚类算法，这是用java实现k-means的源码，其中包括了测试数据文件
上传时间： 2014-01-11
上传用户：lizhizheng88
模式识别中K均值算法的示例程序，可对一组数据分类并图形输出分类结果。
上传时间： 2013-12-23
上传用户：yph853211
c＋＋_mfc入门j
标签： mfc
上传时间： 2016-02-02
上传用户：牛布牛
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
标签： the decision clusters Cluster
上传时间： 2013-12-21
上传用户：gxmm
主要是KNN（the k-nearest neighbor algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.
标签： quantization k-nearest algorithm decision
上传时间： 2016-02-07
上传用户：zhyiroy
Jean J.Labrosse又一部力作《Embedded System Building Blocks》的光盘
标签： Embedded Building Labrosse Blocks
上传时间： 2013-12-16
上传用户：13517191407
这是一个关于K均值的聚类算法希望对大家有用
上传时间： 2016-02-15
上传用户：ma1301115706
Floyd-Warshall算法描述 1)适用范围： a)APSP(All Pairs Shortest Paths) b)稠密图效果最佳 c)边权可正可负 2)算法描述： a)初始化：dis[u,v]=w[u,v] b)For k:=1 to n For i:=1 to n For j:=1 to n If dis[i,j]>dis[i,k]+dis[k,j] Then Dis[I,j]:=dis[I,k]+dis[k,j] c)算法结束：dis即为所有点对的最短路径矩阵 3)算法小结：此算法简单有效，由于三重循环结构紧凑，对于稠密图，效率要高于执行|V|次Dijkstra算法。时间复杂度O(n^3)。 考虑下列变形：如(I,j)∈E则dis[I,j]初始为1,else初始为0，这样的Floyd算法最后的最短路径矩阵即成为一个判断I,j是否有通路的矩阵。更简单的，我们可以把dis设成boolean类型，则每次可以用“dis[I,j]:=dis[I,j]or(dis[I,k]and dis[k,j])”来代替算法描述中的蓝色部分，可以更直观地得到I,j的连通情况。
标签： Floyd-Warshall Shortest Pairs Paths
上传时间： 2013-12-01
上传用户：dyctj
选择第k小的元素，c语言 partition 要好好看看 理解函数意思
标签： 元素
上传时间： 2016-02-19
上传用户：ukuk
