Matlab 聚类和数据格式
从上一个问题开始 FCM 聚类数字数据和 csv/excel 文件< /a> 我现在试图弄清楚如何获取输出的信息并创建一个可用的 .dat 文件以在 matlab 中进行聚类。
%# read the list of features
fid = fopen('kddcup.names','rt');
C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1);
fclose(fid);
%# determine type of features
C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end
attribNom = [ismember(C{2},'symbolic');true]; %# nominal features
%# build format string used to read/parse the actual data
frmt = cell(1,numel(C{1}));
frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number
frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as string
frmt = [frmt{:}];
frmt = [frmt '%s']; %# add the class attribute
%# read dataset
fid = fopen('kddcup.data','rt');
C = textscan(fid, frmt, 'Delimiter',',');
fclose(fid);
%# convert nominal attributes to numeric
ind = find(attribNom);
G = cell(numel(ind),1);
for i=1:numel(ind)
[C{ind(i)},G{i}] = grp2idx( C{ind(i)} );
end
%# all numeric dataset
M = cell2mat(C);
我有几种类型的数据,如下所示:
我尝试了以下方法来创建 .dat 文件但出现了错误:
>> a = load('matlab.mat');
>> save 'matlab.dat' a -ascii
Warning: Attempt to write an unsupported data type
to an ASCII file.
Variable 'a' not written to file.
>> a = load('data.mat');
>> save 'matlab.dat' a -ascii
Warning: Attempt to write an unsupported data type
to an ASCII file.
Variable 'a' not written to file.
>> save 'matlab.dat' a
>> findcluster('matlab.dat')
??? Error using ==> load
Number of columns on line 1 of ASCII file
C:\Users\Garrith\Documents\MATLAB\matlab.dat
must be the same as previous lines.
Error in ==> findcluster>localloadfile at 471
load(filename);
Error in ==> findcluster at 160
localloadfile(filename, param);
Matlabs聚类工具适用于多维数据集,但仅显示在两个 方面。然后,您使用 x 和 y 轴进行比较,但我不太确定是否能够根据当前数据创建聚类二维分析?
我需要做的是规范化我上一篇文章中的 m 文件 FCM 聚类数值数据和 csv/excel 文件
要标准化数据:
查找最小和最大数据集
归一化比例最小值和最大值
数据集中的数字
归一化值
所以第一个问题是如何找到数据集中的最小和最大数字(m)
步骤1: 找到数据集中的最大和最小值,并用变量大写 A 和大写 B 表示它们:
Lets say minimum number A = 92000
and max number say B = 64525000
第 2 步标准化 确定最小和最大数字并将变量设置为小写 a 和 b 不确定如何在 matlab 中执行此操作(不确定如何标准化数据)
set the minimum = a = 1
set the maximum = b = 10
第 3 步 使用以下方程计算任意数字 x 的归一化值
A = 92000
B = 64525000
a = 1
b = 10
x = 2214000
a + (x - A)(b - a)/(B - A)
1+(2214000 - 92000)(10-1)/(6425000 - 92000)
= 4.01
Leading on from a previous question FCM Clustering numeric data and csv/excel file Im now trying to figure out how to take the outputed information and create a workable .dat file for use with clustering in matlab.
%# read the list of features
fid = fopen('kddcup.names','rt');
C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1);
fclose(fid);
%# determine type of features
C{2} = regexprep(C{2}, '.
I have several types of data which looks like this:
I tried the below method to create a .dat file but came up with the error:
>> a = load('matlab.mat');
>> save 'matlab.dat' a -ascii
Warning: Attempt to write an unsupported data type
to an ASCII file.
Variable 'a' not written to file.
>> a = load('data.mat');
>> save 'matlab.dat' a -ascii
Warning: Attempt to write an unsupported data type
to an ASCII file.
Variable 'a' not written to file.
>> save 'matlab.dat' a
>> findcluster('matlab.dat')
??? Error using ==> load
Number of columns on line 1 of ASCII file
C:\Users\Garrith\Documents\MATLAB\matlab.dat
must be the same as previous lines.
Error in ==> findcluster>localloadfile at 471
load(filename);
Error in ==> findcluster at 160
localloadfile(filename, param);
Matlabs clustering tool works on multi-dimensional data sets, but only displays on two
dimensions. You then use the x and y axis to compare against but im not quite sure if I will be able to create a clustering 2d analysis from the current data?
What I need to do is normalize the m file from my previous post FCM Clustering numeric data and csv/excel file
To normalize the data:
-
find the minimum and maximum dataset
-
Normalized scale minimum and maximum
-
Number in the data set
-
Normalized value
So first question is how do I find the minimum and maximum numbers in my dataset(m)
Step 1:
Find the largest and smallest values in the data set and represent them with the variables capital A and capital B:
Lets say minimum number A = 92000
and max number say B = 64525000
Step 2 normalize
Identify the smallest and largest numbers and set the variables to lower case a and b
unsure how to do this in matlab (not sure how you normalize the data to start with)
set the minimum = a = 1
set the maximum = b = 10
step 3
calculate the normalized value of any number x using the equation
A = 92000
B = 64525000
a = 1
b = 10
x = 2214000
a + (x - A)(b - a)/(B - A)
1+(2214000 - 92000)(10-1)/(6425000 - 92000)
= 4.01
,''); %# remove "." at the end
attribNom = [ismember(C{2},'symbolic');true]; %# nominal features
%# build format string used to read/parse the actual data
frmt = cell(1,numel(C{1}));
frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number
frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as string
frmt = [frmt{:}];
frmt = [frmt '%s']; %# add the class attribute
%# read dataset
fid = fopen('kddcup.data','rt');
C = textscan(fid, frmt, 'Delimiter',',');
fclose(fid);
%# convert nominal attributes to numeric
ind = find(attribNom);
G = cell(numel(ind),1);
for i=1:numel(ind)
[C{ind(i)},G{i}] = grp2idx( C{ind(i)} );
end
%# all numeric dataset
M = cell2mat(C);
I have several types of data which looks like this:
I tried the below method to create a .dat file but came up with the error:
Matlabs clustering tool works on multi-dimensional data sets, but only displays on two
dimensions. You then use the x and y axis to compare against but im not quite sure if I will be able to create a clustering 2d analysis from the current data?
What I need to do is normalize the m file from my previous post FCM Clustering numeric data and csv/excel file
To normalize the data:
find the minimum and maximum dataset
Normalized scale minimum and maximum
Number in the data set
Normalized value
So first question is how do I find the minimum and maximum numbers in my dataset(m)
Step 1:
Find the largest and smallest values in the data set and represent them with the variables capital A and capital B:
Step 2 normalize
Identify the smallest and largest numbers and set the variables to lower case a and b
unsure how to do this in matlab (not sure how you normalize the data to start with)
step 3
calculate the normalized value of any number x using the equation
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查看问题中间的错误。
a = load(matfile)
返回一个结构,基于 ASCII 的 MAT 文件格式不支持该结构。尝试阅读文档。Looking at the errors in the middle of your question.
a = load(matfile)
returns a structure, which is not supported by the ASCII-based MAT-file format. Try reading the documentation.