Partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. Clustered-standard-errors and/or cluster-samples should be tagged as such; do not use the "clustering" tag for them.

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2
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1answer
83 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
2
votes
1answer
29 views

How does the Gower distance calculate the difference between binary variables'?

I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. ...
-2
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0answers
20 views

What to do after calculating Gower for clustering? [on hold]

I used daisy function with Gower metric and found a matrix in R. What is next step for clustering?
0
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0answers
15 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 ...
8
votes
1answer
1k views

Hierarchical clustering with mixed type data - what distance/similarity to use?

In my dataset we have both continuous and naturally discrete variables. I want to know whether we can do hierarchical clustering using both type of variables. And if yes, what distance measure is ...
0
votes
1answer
247 views

Outlier detection using clustering and dissimilarity matrix in R

I have some problems in finding the outliers using clustering. The data.frame is ~20000 observations and each row has mixed types of variables(numeric, nominal and binary). What I want to do is to ...
0
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0answers
17 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 ...
2
votes
3answers
527 views

Rand index calculation

I'm trying to figure out how to calculate the Rand Index of a cluster algorithm, but I'm stuck at the point how to calculate the true and false negatives. At the moment I'm using the example from the ...
0
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1answer
189 views

Gaussian neighborhood function and non linear learning rate for self-organizing map in R

I've been working on SOMs and how to get the best clustering results. One approach could be to try many runs and choose the clustering with the lowest within sum of squared errors. However, I do not ...
7
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3answers
2k views

Mixture Models and Dirichlet Process Mixtures (beginner lectures or papers)

In the context of online clustering, I often find many papers talking about: "dirichlet process" and "finite/infinite mixture models". Given that I've never used or read about dirichlet process or ...
2
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1answer
555 views

Cluster analysis on weighted survey data with continuous and categorical variables

I am trying to perform cluster analysis on survey data where each respondent has answered several questions, some of which have categorical answers ("blue" "pink" "green" etc) and some of which have ...
0
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0answers
25 views

Inter-cluster variance

Can you please help me understand how is inter-cluster (between clusters) variance defined? As opposed to intra-cluster variance which is pretty straightforward, I have not managed to found a clear ...
1
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1answer
69 views

Evaluation measures of overlapping clustering

I have a dataset of Facebook users and a set of different clustering algorithms. The project goal is to draw up a rank between these algorithms in order to understand which of them are the good ones. ...
4
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1answer
1k views

PyMC for nonparametric clustering: Dirichlet process to estimate Gaussian mixture's parameters fails to cluster

Problem setup One of the first toy problems I wanted to apply PyMC to is nonparametric clustering: given some data, model it as a Gaussian mixture, and learn the number of clusters and each cluster's ...
0
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1answer
43 views

How to visualize cluster data in a scatter way

Having a clustered dataset, I want to visualize a scatter plot for two fields so every cluster is shown on the plane by its mean value (also good to have a radius equal to std). How does one do this ...
2
votes
2answers
97 views

Comparison of close data sets

I'm studying around 100 sets of temperature ($N_{sample}=500$), which depends $4$ explicative variables such as power or speed. The dependency is always the same in each set, but sometimes the mean ...
0
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1answer
41 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: ...
4
votes
1answer
670 views

Validate cluster analysis in R

I am trying to validate hierarchical cluster analysis result following a paper by Guy Brock, et al. clValid: An R Package for Cluster Validation (pdf). Do I have to use all these methods? What are the ...
2
votes
1answer
69 views

Detecting strong currents in a sparse directed graph

I have a very large, sparse, weighted, directed graph. The structure is such that it mainly consists of strings of nodes connected with highly weighted edges. These strings can be connected by weak ...
2
votes
1answer
33 views

Weighted cases in a cluster analysis for cases in SPSS

I am conducting a cluster analysis (of cases) for a database which has weight attributed to the individual cases to ensure that it mirrors the general population in terms of sociodemographic ...
0
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0answers
19 views

Validating feature patterns of subgroups in clustering

I am trying to identify the typical developmental trajectories that participants follow in a learning task. The data set includes the performance of 1,000 learners over 10 trials each and, say, looks ...
1
vote
1answer
76 views

K-means cluster Analysis and 4-point Likert Scales

Is there a concern using a 4-point likert-type scale (i.e., agreement) when attempting a cluster analysis using k-means clustering? Most of the data for the items in my data set are favorable (e.g., ...
0
votes
1answer
268 views

An incremental Gaussian mixture model

Question 1: Suppose that data is modelled by a mixture of K probability distributions which are actually Gaussians. $P(x_i|\theta_j)$ is the probability density of the j'th cluster, for which the ...
0
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0answers
12 views

How to count overall similarity? [closed]

What I want to do is calculate the overall similarity. How can I do that?. For example, I have this clusters with the number of the cluster member, how can I calculate the overall similarity? ...
0
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1answer
17 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 ...
1
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1answer
49 views

Cluster interpretation

I'm running flat clustering algorithm on my dataset that contains numeric (not categorical) data. Is there a method that can give me interpretation of clusters, and emphasize what are the most ...
3
votes
2answers
320 views

Clustering of points based on vector feature similarities in R

I have as an input a number of points that I need to partition into clusters. Each point has a number of features that are ideally to be used to find the similarity between each point and the others. ...
1
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2answers
192 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?
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1answer
39 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 ...
-1
votes
1answer
23 views

How to map clustering results to known groups?

I have a data set, which form 3 known groups. I performed k-means clustering algorithm on the data set, setting the number of clusters to be 3 as well. I end up with 3 groups by k-means. Wishing to ...
0
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2answers
69 views

Proper Statistical Test for Binary Data

I looking for the best statistical test to apply in a particular situation and I hope I can find here the answer(s) I'm looking for. First of all some details: I'm studying 33 different mutants of a ...
2
votes
2answers
113 views

Relevance of overall absolute values in covariance analysis of two variables

I am performing K means clustering on a gene expression dataset. I am aware of the fact that the Pearson correlation metric allows to group trends or patterns irrespective of their overall level of ...
0
votes
1answer
104 views

Interpretation of NbClust result

The plots show the output of NbClust(). By looking at the plot, is that correct to say that k=5 is the optimal number of ...
-1
votes
0answers
15 views

Cluster analysis (not centroid-based, fuzzy, Matlab)

could you please help me find a cluster analysis algorithm that has the following properties: can deal with "entangled" data ...
6
votes
1answer
154 views

How is this “United States of Reddit” graph created?

Below is a graph from p. 202 of Christian Rudder's Dataclysm, though it was made by James Dowdell. It illustrates the relationships betweens various top 200 subreddits, which are areas of interest on ...
1
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1answer
110 views

Validation of clustering results through correlation maps

How can I compare correlation maps independently to the number of clusters in terms of measuring the 'quality' of well separating (uncorrelated) clusters, i.e. a criterion to maximize the ...
0
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0answers
26 views

KNN - does it use centroids?

I'm really confused now having read so many articles on KNN, I can't help but think I'm missing the obvious. Let's say I have persons P1 and P2, P3 are represented with attributes of height, weight ...
3
votes
1answer
139 views

Distance between two Gaussian mixtures to evaluate cluster solutions

I'm running a quick simulation to compare different clustering methods, and currently hit a snag trying to evaluate the cluster solutions. I know of various validation metrics (many found in ...
1
vote
1answer
30 views

Tool form Hierarchical clustering

I'm trying to perform a hierarchical Clustering Analysis in a dataset of 40 attributes and +70,000 records, which is mostly composed by categorical variables. I've used Matlab and RapidMiner to ...
1
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1answer
17 views

Matrix reordering algorithms

I have a similarity matrix and I would like to apply an algorithm that reorders the entries based on their similarity. The aim is to move entries with high similarity closer to the main diagonal. The ...
1
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1answer
34 views

Clustering based anomaly detection

I'm trying to implement anomaly detection based on clustering. I'm hopping for confirmation of my approach, and I'm exposing my idea, being aware that I could have miss something in my analysis, so ...
0
votes
0answers
25 views

Top K variable that represent entire dataset

There are 100 variables in the dataset. Also, i have extracted some additional information about each variable viz Var1 is correlated (Pearson correlation) to Var21,Var25,Var34,Var45,Var55 ; Var2 is ...
5
votes
2answers
272 views

Can sub-optimality of various hierarchical clustering methods be assessed or ranked?

Classic agglomerative hierarchical clustering methods are based on a greedy algorithm. This means that they (many of them) are prone to give sub-optimal solutions instead of the global optimum result, ...
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0answers
26 views

Correlation space as preprocess to hierarchical clustering

Say you have data matrix X of size NxP where N is the number of samples and ...
0
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0answers
4 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 ...
0
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0answers
60 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 ...
-1
votes
1answer
56 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 ...
7
votes
2answers
251 views

Memory requirements of $k$-means clustering

Can anyone tell me the factors that affect the memory requirements of $k$-means clustering with a bit of explanation?
2
votes
2answers
83 views

How can I evaluate the performance of a system that generates word clusters?

The word2vec tool uses deep learning to compute vector representations of words. They've mentioned that - "The word vectors can be also used for deriving word classes from huge data sets. This is ...
2
votes
1answer
117 views

Agreement of clustered data

I have the following situation: I have analyzed several data curves from a group of patients (16 curves per patient) with different analysis methods and want to test for the agreement of the methods. ...