Tagged Questions

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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16 views

Can we use kNN and k-mean at a same time?

I Get dataset of neighbours using kNN and then I want to apply k-mean on that dataset. By using this, is it possible that I get more accurate result? Is it logically correct that use kNN and then ...
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1answer
29 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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34 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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27 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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2answers
40 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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63 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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18 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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1answer
24 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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1answer
87 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
108 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 ...
0
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1answer
62 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: ...
0
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1answer
21 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
49 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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16 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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1answer
62 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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1answer
41 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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0answers
13 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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114 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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70 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
68 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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26 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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2answers
89 views

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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0answers
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 ...
5
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3answers
191 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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2answers
35 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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24 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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2answers
32 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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1answer
76 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 ...
4
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2answers
127 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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2answers
50 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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0answers
78 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 ...
0
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1answer
59 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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0answers
30 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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27 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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115 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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0answers
10 views

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 ...
0
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1answer
77 views

Spherical K-means Clustering in R

I have a large data set that I would like to cluster using spherical K means algorithm. However, I am relatively new to this subject and R in general. Most of my knowledge is self taught and I am ...
0
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121 views

I find very different results using a k-means or two-step clustering method. How is this?

I want to use a cluster analysis (CA) in SPSS to define different profiles in my dataset. I am using different continuous variables for this, including several neuropsychiatric measures. I am new in ...
0
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1answer
21 views

Spectral clustering using Technics other than kmeans

In spectral clustering, the algorithm suggests performing K-means to k eigenvectors of the resulted Laplacian matrix. My question is: 'Can I use other clustering algorithms such as K-medoids or other ...
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2answers
316 views

k-means vs k-median?

I know there is k-means clustering algorithm and k-median. One that uses the mean as the center of the cluster and the other uses the median. My question is: when/where to use which?
4
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3answers
168 views

K-means cluster analysis with K=2 as a binary classifier

I used two variables, height and weight, and using K-means cluster analysis with $K=2$, two clusters were obtained. I used $K=2$, as the observations either belong to men or women. I then compared the ...
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1answer
75 views

k-means clustering on percentages

Can we do k-means clustering on percentage data (like 56%, 44%, 22%, 13%, etc.)? There is a data set, and data in various parts are measured in percentages.
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1answer
49 views

k-means in R generates same number of clusters but different cluster label

Hi there I am running a k-means code in R with the same data and with the same number of clusters, in this case 3, but each time that I run the code, the cluster label changes, for example. In the ...
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1answer
39 views

A clustering and classification question

I'm trying to classify my set of data into two classes (introvert / extrovert). I was thinking of using a decision tree at first, but I don't have any potential known results in order to create my ...
0
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1answer
36 views

Classifying a set of photos to places

I want to cluster photos and map them to places. As input I have Photos with locations (lat, long) Places - some as (imprecise) bounding boxes, some just as points, maybe others as bounding ...
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2answers
71 views

clustering accuracy

I have a general doubt regarding clustering. I have a data set of size 1196*18675. where 1196 is the no of documents. I am trying to cluster the data with k=7 using k-means. Each time the clustered ...
3
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1answer
56 views

K-means metrics

I have read through the scikit learn documentation and Googled to no avail. I have 2000 data sets, clustered as the picture shows. Some of the clusters, as shown, are wrong, here the red cluster. I ...
0
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0answers
20 views

Turning MiniBatchKMeans into Fuzzy MiniBatchKMeans

I'm using Scikit-Learn, which has an implementation of MiniBatchKMeans. I'm very inexperienced with ML, so I'm wondering how (if ...
2
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1answer
43 views

Which clustering technique to use for a temporal dataset?

I have seen a similar question but thought I'd ask my own to hopefully garner some usefull feedback. Basically, I have a large temporal dataset, consisting of domestic smart energy meter use ...