K-mean Clustering

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MAT NIZAM UTI 2021-11-9

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编辑： MAT NIZAM UTI 2021-11-18

Hi Everyone, can someone help me on how to use the K-mean clustering or perhaps share with me the suitable coding use to cluster wind speed data. I hava wind speed data in the form of Latitude, Longitude, Wind Speed. I want to cluster the data into 3 groups.

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Image Analyst 2021-11-12

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If you have all the lat and lon values, then just put each into kmeans separately:

numColumns = 26; % Or however many columns you know there to be.
[xIndexes, xCentroids] = kmeans(lon, numColumns);
numRows = 50; % Or however many rows you know there to be.
[yIndexes, yCentroids] = kmeans(lat, numRows);

The values of the columns (x or longitude values) will be in xCentroids.

The values of the rows (y or lat values) will be in yCentroids.

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Image Analyst 2021-11-14

在 MATLAB Online 中打开

WIND_26YEARS.csv

, it doesn't make sense. Why is Y1 random? And why is Y1 a row vector while X1 is a column vector? Even if Y1 was also a column vector, it doesn't make sense to cluster random data.

And where is K in your kmeans() call? You read in the badly-named "k" but don't even consider it when you're doing kmeans? Did you realize you're calling kmeans without your data???

I would have fixed it for you but I realized I don't know what each row of k represents.

% Demo by Image Analyst
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
% Read in data
k = readmatrix('WIND_26YEARS.csv');
% Plot raw data
subplot(3, 1, 1);
plot(k, 'b-')
grid on;
xlabel('index', 'FontSize',fontSize);
ylabel('Value of k', 'FontSize',fontSize)
title('All the k Values', 'FontSize',fontSize)
% Plot histogram of k data.
subplot(3, 1, 2);
histogram(k);
grid on;
xlabel('k', 'FontSize',fontSize);
ylabel('Count', 'FontSize',fontSize)
title('Distribution of k.  Note no clusters!', 'FontSize',fontSize)
% Original poster's (bad) code below:
subplot(3, 1, 3);
X1=(1:6943)';
Y1=randn(6943,1);
numClusters=3;
idx1=kmeans([X1, Y1],numClusters,'Replicates',5);
pointclust=repmat(idx1,1,numClusters)==repmat(1:numClusters,numel(idx1),1);
colors=hsv(numClusters);
for j=1:numClusters
    plot(X1(pointclust(:,j)),Y1(pointclust(:,j)),'Color',colors(j,:));
    if j==1
        hold on;
    end
end
hold off;
xlabel('X1', 'FontSize',fontSize);
ylabel('Y1', 'FontSize',fontSize)
title('Clusters are in different colors', 'FontSize',fontSize)
grid on;
g = gcf;
g.WindowState = 'maximized'

Image Analyst 2021-11-17

在 MATLAB Online 中打开

WIND_26YEARS.csv

I think you uploaded a different data file than you think. Look what happens when I run this code:

% Read in data
k = readmatrix('WIND_26YEARS.csv');
k = readmatrix('WIND_26YEARS.csv');
lats = k(1:3:end); % 2315 long
lons = k(2:3:end); % 2314 long
speeds = k(3:3:end); % 2314 long
whos k
whos lats
whos lons
whos speeds

Name Size Bytes Class Attributes

k 6943x1 55544 double

Name Size Bytes Class Attributes

lats 2315x1 18520 double

Name Size Bytes Class Attributes

lons 2314x1 18512 double

Name Size Bytes Class Attributes

speeds 2314x1 18512 double

As you can see, k is not a multiple of 3 so lats is one element longer than the other two. Why is that?

Moreover, the wind speeds are practically the same value as lats and lons (they are all around values 0-8), which is suspicious unless you measured the wind near the north pole. Please attach the actual data.

Image Analyst 2021-11-18

So can we just take the first 2314 values and ignore the extra lat?

MAT NIZAM UTI 2021-11-18

编辑：MAT NIZAM UTI 2021-11-18

Sure..well I dont really know how the matlab works, because after comparing the actual values and the after read values, both lons and speeds were different with the actual data.

https://drive.google.com/drive/folders/1tFOl0ZHQo4XzB-VGvi-LBLPg_lERG98u (this is my very actual data) Column C until LB is the wind speeds values.

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H R 2021-11-9

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1582194-k-mean-clustering#answer_827124

在 MATLAB Online 中打开

Plese see: https://www.mathworks.com/help/stats/kmeans.html.

If your data is in a matrix format X, then you can use the following:

[idx,C] = kmeans(X,3,'Distance','cityblock','Replicates',5);

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H R 2021-11-12

Yes, every thing is possible (even using 1D data) , but you have to finally check what you are looking for from the clustering task and check if the outcome makes sense to you.

MAT NIZAM UTI 2021-11-14

编辑：Image Analyst 2021-11-14

在 MATLAB Online 中打开

WIND_26YEARS.csv

Here is my coding, and I have an error on it

Error using horzcat

Dimensions of matrices being concatenated are not consistent.

Error in k_mean (line 7)

idx1=kmeans([X1 Y1],numClusters,'Replicates',5);

This is the code:

k = xlsread('WIND_26YEARS.csv');
X1=(1:6943);
Y1=randn(6943,1); 
numClusters=3;
idx1=kmeans([X1 Y1],numClusters,'Replicates',5);
pointclust=repmat(idx1,1,numClusters)==repmat(1:numClusters,numel(idx1),1);
colors=hsv(numClusters);  
for j=1:numClusters,
    plot(X1(pointclust(:,j)),Y1(pointclust(:,j)),'Color',colors(j,:));
    if j==1,
        hold on;
    end;
end,
hold off;

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K-mean Clustering

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