-
KMEANS
This directory contains code implementing the K-means algorithm. Source code
may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS
program accepts input consisting of vectors and calculates the given
number of cluster centers using the K-means algorithm. Output is
directed to the screen.
Usage for KMEANS is:
KMEANS SOURCEFILE <enter>
The format of the source file is:
NPat - Number of patterns (int)
SizeVect - Size of vector (int)
NClust - Number of cluster centers(int)
vect[1,1] ... vect[1,SizeVect] - vector 1 (real)
vect[2,1] ... vect[2,SizeVect] - vector 2 (real)
. .
. .
. .
vect[NPat,1] ... vect[NClust,SizeVector] - vector N (real)
To compile:
ICC KMEANS.CPP <enter>
(This directory contains code implementing the K-means algorithm. Source code
may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS
program accepts input consisting of vectors and calculates the given
number of cluster centers using the K-means algorithm. Output is
directed to the screen.
Usage for KMEANS is:
KMEANS SOURCEFILE <enter>
The format of the source file is:
NPat - Number of patterns (int)
SizeVect - Size of vector (int)
NClust - Number of cluster centers(int)
vect[1,1] ... vect[1,SizeVect] - vector 1 (real)
vect[2,1] ... vect[2,SizeVect] - vector 2 (real)
. .
. .
. .
vect[NPat,1] ... vect[NClust,SizeVector]- vector N (real)
To compile:
ICC KMEANS.CPP <enter>
)
- 2013-01-05 23:11:23下载
- 积分：1
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0123
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(Statistical analysis of data and graphical data statistical analysis of open dialog, the dialog box can be data minimum, maximum, average, median and standard deviation and so on.)
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function [p, table] = anova_rm(X, displayopt)Single factor, repeated measures ANOVA.)
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全方位的指导手册 (Building geometry
Setting boundary condition types)
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Desktop
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- 2019-02-10 15:37:57下载
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单纯形法Matlab程序-2016-11-17
一般线性规划问题具有线性方程组的变量数大于方程个数，这时会有不定的解。当决策变量个数n和约束条件个数m较大时，单纯形法是求解线性规划问题的通用方法。
从线性方程组找出一个个的单纯形，每一个单纯形可以求得一组解，然后再判断该解使目标函数值是增大还是变小了，决定下一步选择的单纯形。通过优化迭代，直到目标函数实现最大或最小值(In general linear programming problems, the number of variables with linear equations is greater than the number of equations. When the number of decision variables n and constraint number m are large, simplex method is the general method for solving linear programming problems.
Find out one by one from the linear equations of the simplex, each a simplex can get a set of solution, and then concludes that the solution is the objective function value increases or smaller and decided to choose the next simplex. By optimizing iteration, until the target function achieves the maximum or minimum value.)
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Dijkstra
求数组最长递增子序列算法。输入一个数组，输出其最大递增子序列(Array for the longest increasing subsequence algorithm. An array of input and output its maximum incremental sequence)
- 2007-08-07 16:14:13下载
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