k-means is a family of cluster analysis methods in which you specify the number of clusters you expect. This is as opposed to hierarchical cluster analysis methods.

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Clustering into teams of fixed size

There is a particular team-based video game that exposes a ladder of individual ratings for each player that looks like this (player, rating, wins, losses): A, 2000, 35, 12 B, 1900, 41, 19 C, 1800, ...
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6 views

Clusteriod questions

I would like to clear some things up because I'm confusing everything. A $clusteriod$ is a coordinate for the mean value of a cluster? So if I have a 2-d .csv file I wish to perform kmeans, the ...
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24 views

Cluster Sequences of data with different length

I need to cluster sequences of data that have different length. I am using Matlab and my first question is related to the method. Is KMeans sufficient to achieve this? IN KMeans I have to use the ...
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Initial clusters in Kmeans clustering using mahout

I am trying to perform kmeans algorithm on data using . The option that has to be passed while running need a path to initial clusters. Can anyone tell me how can we have initial clusters even before ...
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23 views

K-means clustering with one column

I'm new to the k-means clustering algorithm. I have the following data: 228,796 321,523 222,664 257,265 4,174 8,25 327,531 ... These are total electricity ...
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29 views

Can I use k-means with a distance matrix composed of percentages? [duplicate]

I have objects o1, o2,...,on and for each pair I calculate a value that measures the pair's difference. This is a percentage, so for example o1o2 differ by 56%. Now I want to cluster this data. I can ...
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15 views

“Hierarchical k-means” wrong sample assignment

I am working on a hierarchical k-means scheme which is translated into sequential k-means in my case. Let say I have 10k samples (objects to cluster) which I want ...
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30 views

Middle point between k-means and DBSCAN in R

I have a big data sample of unrelated events in lon,lat,date format (booking locations to dispatch). I am trying to divide these events into clusters (k=50) where I ...
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22 views

Unnatural clustering with known clusters shapes and optimization criteria

My question is similar to this question Clustering with shape prior, but with additional information. The second answer suggests a mixture model approach to this problem, which is something like ...
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51 views

What kernel function can be used to project data into a feature space that is a “circle”?

I am working with cyclical data (Days 1-7, hours 1-24). I want to project it into a feature space that can understand that 1 and 7 are close days and 1 and 24 are closer than 22 and 24, etc, and then ...
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11 views

Data set with negative silhouette

I want to construct data set 𝐷 in 2 dimension, with a clustering {𝐶1, 𝐶2} computed by k-means with the property: which full fills the condition: There exists a point $𝑜∈𝐷$ with a negative ...
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41 views

Result of K-Means Algorithm Not Desired

I am learning about K-means algorithm, and I have generated a dataset with 150000 data points, with 10000 points per cluster. (Scatter plot at the bottom) When I run K-means on the dataset, I first ...
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27 views

Efficient weighted 1D Clustering (Grouping)

I'm dealing with the simple problem of grouping a set of 1-dimensional data (1 feature) according to its distribution in the 1-D space. I know exactly the number of groups I will like to get. So for ...
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60 views

k-mean clustering of week-times

I have data of meeting times. The data has weekday and hour of the day. I want to cluster the meeting times (I have reason to believe there are two different kinds of meetings that tend to occur at ...
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40 views

Why is k-medians typically used with Manhattan rather than Euclidean distance?

K-medians is typically used with Manhattan distance rather than Euclidean distance. Why is this?
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44 views

K means clustering of variable with multiple values

I have a sample data below that is from a large data set, where each participant is given multiple condition for scoring. ...
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29 views

K-means and maximum likelihood!

Is there any relation between k-means and the maximum-likelihood estimate in unsupervised learning? Any references would be appreciates! Thank you!
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65 views

Clustering a long list of strings (words) into similarity groups

I have the following problem at hand: I have a very long list of words, possibly names, surnames, etc. I need to cluster this word list, such that similar words, for example words with similar edit ...
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86 views

How is Weka calculating nominal attributes for K-means clustering?

I have both numeric and nominal variables in my dataset. Before applying clustering in Weka, I specified nominal variables to Weka and select K-means clustering. It is good that my nominal data seems ...
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20 views

Selecting the right BIC value

I'm using the hddc for an assignment to find the optimal number of clusters. The dataset is 9-dimensional and consists of 200.000 rows, however, the BIC values that I'm getting are really high. How ...
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28 views

k-means for set of integers [duplicate]

I'm not really sure where to begin with this but for a simplified example I have a set of integers: {11, 22, 3, 12, 1, 23, 21, 13, 2} I need to partition these into K=3 clusters with initial ...
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246 views

K-means on cosine similarities vs. Euclidean distance (LSA)

I am using latent semantic analysis to represent a corpus of documents in lower dimensional space. I want to cluster these documents into two groups using k-means. Several years ago, I did this using ...
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1answer
236 views

Calculate P value for the correlation coefficient

I would like to understand how people add the P value on a figure for means (Y axis) by age, volume or any other variable (x axis). How did they calculate the P value here? Please check the following ...
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94 views

k-means cluster, How to re-calculate centroid when using cosine similarity?

I have a requirement using k-means cluster method with cosine similarity instead of Euclidean distance. for example: ...
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23 views

What is the easiest way to evaluate k-means clustering?

I did clustering with k-means, but I haven't complete my project, now I have to evaluate the result of the k-means clustering, and I want to do that with the easiest way. does anyone have any ...
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1answer
52 views

Best clustering technique for outlier detection?

I have around 15-20 points every second, and I would like to detect outliers based on -their density along x-axis , that means if I am using k-mean clustering then I specify that in x-direction max ...
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20 views

Kalman filter before or after outlier removal?

I am getting radar data points in form of (x,y) coordinate system relative to my position every ms.[around 10-15 data points]. Now, inorder to have better position estimate of the points, I would like ...
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67 views

Why did K means clustering do a poor job in R

I am trying to implement K means clustering in R, Here is what my data look like: ...
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46 views

Data normalization in k-means and svm

Generally if I want to normalize my data in which direction I should normalize (subtracting mean and dividing by std)? Lets say I have a data matrix D (...
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15 views

Hand Coordinates Clustering for vector quantization

I've a sequence of pitch, yaw, roll of the hand, plus pitch and yaw of the fingers. So i got a 13-dimensional vector. Which is the best way to understand how to cluster these data in order to perform ...
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150 views

Replicability of Cluster Analysis Solutions / Does Cluster Solution Order Matter

I am performing cluster analysis on a sample (psychology) and I would like to determine how to check the replicability of the cluster solutions. More specifically, I am following the protocol laid out ...
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91 views

K-means as a limit case of EM algorithm for Gaussian mixtures with covariances $\epsilon^2 I$ going to $0$

My goal is to see that K-means algorithm is in fact Expectation-Maximization algorithm for Gaussian mixtures in which all components have covariance $\sigma^2 I$ in the limit as $\lim_{\sigma \to 0}$. ...
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1answer
84 views

Determining number of clusters K-means [duplicate]

I would like to automatically determine the number of clusters for K-means. I have read that elbow method could be used for that. The thing that confuses me is - I have to rerun algorithm while ...
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9 views

Mean of vectors minimizes L2-norm [duplicate]

Recently introduced to data mining and am trying to understand how the mean of vectors minimizes L2-Norm/Euclidean distance. I've tried googling it and can't seem to find a proof as to how something ...
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32 views

R Clustering Evaluation (Adaptive Kmeans)

i know there are several threads about this topic, but most i read, most i get confused. I'm doing a project that consists in clustering some data (news articles). I used adaptive Kmeans ...
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K-means clustering in Matlab for feature selection

I am doing feature selection on a cancer data- set which is multidimensional (27803 * 84). I want to try with k-means clustering algorithm in Matlab but how do I decide how many clusters do I want? ...
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16 views

How to split a class which is not very cohesive?

Using the silhouette width metric I can find out as to how well each object lies within its class after classification is done. I next find the average silhouette width of objects within a class and ...
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296 views

Appropriateness of ANOVA after k-means cluster analysis

The notification after the ANOVA table after K-means analysis indicates that significance levels should not be looked at as the test of equal means, as the cluster solution has been derived based on ...
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39 views

Kmeans cluster size change quite a bit on each run

I am running a kmeans on a sample size of 1000 data. The data is scaled (z). When I run kmeans(df, nstart=25, centers=5)- it runs and I can get the size of each cluster. The largest group has 620 in ...
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31 views

Kmeans plotting on discriminant components

When you plot a kmeans model (in R) with the plotcluster() function, it plots the clusters against the axis of the 1st and 2nd discriminant components (dc). In reading about these axis- some state ...
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33 views

How to compare two clusterings generated by two clustering approaches

I am currently working on a modification of a clustering algorithm to suit my problem domain. I want to know which methods are available for me to compare the centroids generated from the two ...
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94 views

Outlier detection using k-means in a binary classification problem

I'm using k-means in every class of a binary classification problem and remove samples that have high distance from center of my features (21 features so 21 ...
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147 views

Using k-means with other metrics

So I realize this has been asked before: e.g. What are the use cases related to cluster analysis of different distance metrics? but I've found the answers somewhat contradictory to what is suggested ...
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52 views

What's a good way to mentally visualize n dimensions in a k means

I've been using k-means to do some clustering and one of the ideas I'm struggling with is the n dimensions aspect. If I were clustering housing prices vs sq. feet its just a simple 2d graph. That I ...
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87 views

How do I create clusters with a completely categorical data?

I am working on the project that requires data mining. I have been asked to use R. I have a dataset with all categorical variables and would like to form clusters on that. I am unable to figure out ...
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1answer
71 views

Correlated variables in kmeans clustering

I have a dataset with 3 variables: A, B and C. Now, A and B are ordinal variables (i.e.; the result of two questions measured using a 5-point Likert), whereas B is continuous. A and B are also ...
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31 views

How to measure the similarity of k-means clustering using different datasets?

I run k-means clustering on my dataset (100 samples in total) and partition the data into k=5 clusters. Then I want to test how robust of the k-means can be; however, I haven't got more new data ...
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30 views

How can I evaluate the accuracy of a clustering when I don't have information on the true class labels?

Already classified data set for the t-shirt factory problem I want to calculate the accuracy of my algorithm. I have the training data without any size information and I couldn't find the classified ...
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139 views

Apache Spark - MLlib - K-Means

I want to perform a K-Means task and fail training the model and get kicked out of Sparks scala shell before I get my result metrics. I am not sure if the input format is the problem or something ...
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Calculating the Similarity of Survey Responses

I was wondering if anyone had experimented with different functions for calculating the similarity of two sets of survey responses. I am going to be plugging it into a hierarchical clustering algo and ...