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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26 views

Anomaly detection for one feature vector

I have a $n$-dimensional vector of ordered multiple testing $p$-values and I would like to reject the first values that are under a certain threshold $\alpha$. I am looking at this problem as an ...
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34 views

Determine Number of Clusters Using Silhouette Method and Distance Matrix

I have a tree and its associated distance matrix. Now I want to cut the tree to give a desired number of clusters. Luckily there are a number of methods for determining the number of clusters as ...
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46 views

Unsupervised Random Forest for Visual Codebook generation

I'm trying to apply the bag of visual words approach to make scene classification. I started to use k-means to generate my codebook, but rapidly discovered its limitations. From one codebook ...
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1answer
23 views

On the connection between SSE and absolute deviation from the centroids

Is there any connection between sum of squared error SSE and the absolute deviation from the centroids after clustering. More formally, I have clustered $T=\{x_i\}, i\in\{1,\ldots,n\}$ and the ...
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43 views

Performance of hierarchical clustering for binary data in R

I am trying to use Hierarchical clustering to see how well it performs in classifying a dataset which I previously know its true classification. I am new to clustering in general. I was able to draw ...
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1answer
56 views

Best metric for evaluation of mixture-of-Gaussian clusters on big-data

I have made a new algorithm that is specifically crafted for clustering very large datasets. In order to document it as a research paper, I have to choose one or two internal (no-label) cluster ...
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0answers
5 views

How to identify a subset of effects as the drivers of significant differences?

Okay I will explain this as best as I can. I have an additive risk score for each of my observations (i.e. I'm putting 100 individual effects into a single variable). The means of this risk score ...
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1answer
31 views

How to reduce number of points for clustering

Description I have to find number of clusters for 1D data. All clusters are assumed to have a gaussian distribution (so there is a big number of same points). I have a robust "aglomerative clustering ...
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1answer
33 views

Assigning meaningful cluster name automatically

The objective of my work is to cluster the text documents. Once the documents are clustered, traditionally the system will assign numeric value for the clustered group. For example if I have 5 ...
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1answer
42 views

Identifying subsets for outlier detection in local outlier factor

I am trying to gain better understanding of the idea of local outliers (as discussed in this pdf) and how the function is implemented. Here are the key passages from the pdf: Local outliers: ...
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1answer
41 views

Cluster analysis on time series samples

In the follow-up to this Ways to understand 2-dimensional time-series data I'm working on 2D time series data where two attributes are depth and temperature. When I plotted depth-vs-temp curve and ...
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0answers
54 views

Cophenetic distance matrix to a dendrogram

In hierarchical clustering procedure, a distance matrix is used to construct a dendrogram with an appropriate method of clustering. In the process of constructing a dendrogram, a cophenetic matrix is ...
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1answer
35 views

Extract (ultrametric) distances from hclust or dendrogram

How can the matrix of (ultrametric) distances be extracted from the result of hclust (or a dendrogram in general) in R? The ...
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1answer
49 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., ...
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26 views

Clustering coefficient for a clique

I would like to understand how to solve this exercise about clustering coefficient for a clique. As shown in the picture below if node pairs (a; b), (a; c), (a; d), (b; c), (b; d) are linked, then the ...
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1answer
47 views

Selecting number of clustering classes automatically

I am working in text clustering. I would like to find a way to identify the number of classes for the clustering process automatically rather than proving the number of class manually. Is their any ...
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0answers
14 views

Heuristics for unsupervised or semi-supervised approaches to GIS coordinate data

I have a more conceptual/heuristic question about how to go about formulating a problem in order to take a semi- or unsupervised method of solving it. I'm working on a project with data collected ...
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0answers
27 views

Implementation for Co-Clustering

I am looking for existing implementations for co-clustering (aka biclustering). I came up with biclust function available in MATLAB, but still I am wondering if ...
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1answer
41 views

Combine Clustering and classification

I have a receipt database of a grocery store. I would like to find classes of similar customers based on their receipts and classify people after their shopping to one of these classes. Let us assume ...
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0answers
19 views

Deriving distance function based on multiple variables

This question is in relation to the following answer of yours: How to derive a distance function based on multiple variables for cluster analysis? Suppose I have 7 variables, each quantitative (and ...
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2answers
81 views

Feature / attribute selection for k-means or other clustering

It seems to me that in literature it is assumed that one knows which features / attributes to choose to characterize an item in clustering. If I have a database with items which have many attributes, ...
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1answer
49 views

Different hierarchical clustering results

I'm running a hierarchical clustering on a sample of data using the steps below: ...
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0answers
29 views

Good (2d) visualization of a mixture model clustering

I have a specific problem which I'm surprised I don't find answers on-line and I hope somebody here has a good suggestion for me. I'm working with a large data set which I'm clustering into specific ...
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0answers
32 views

BOW prediction of cluster for training data

I am creating a bag of visual words for classification of videos. I am not using SURF descriptors and that is why I couldn't use OpenCV's BOWImgDescriptorExtractor ...
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2answers
59 views

Cluster Data based on Distribution

I have a list of diseases for my research. For each disease, I have a list of ages for the diseases. "Breast Carcinoma" may be a list of [1,2,2,3,4,5,5,5,5,5] while "Adrenal Cortex Neoplasms" maybe be ...
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63 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...
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1answer
93 views

Is there a decision-tree-like algorithm for unsupervised clustering?

I have a dataset consists of 5 features : A, B, C, D, E. They are all numeric values. Instead of doing a density-based clustering, what I want to do is to cluster the data in a decision-tree-like ...
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1answer
72 views

Clustering without a distance matrix

I've recently completed a project where I used scikit-learn's DBSCAN module to find clusters in relatively short strings of text. I used a custom string similarity ...
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1answer
82 views

Clustering algorithms for extremely sparse data

I am trying to cluster an extremely sparse text corpus, and I know the number of clusters (my data is the title and author list of scientific publications, for which I already know the number of ...
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23 views

Fuzzy C-Means / Latent Dirichlet Allocation

I have to compare the results of document clustering via latent Dirichlet allocation and fuzzy c-means. How can I do this? I've got the option to compare the probabilities the documents are assigned ...
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0answers
57 views

Clustering on a data set with mixed variables

I have a data set consisting of $n$ elements with $d$ features for each element ($x_{i,f}$ means the value for the f-th feature of the i-th element). I would like to cluster this data set into $k$ ...
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0answers
9 views

Clustering with proportional threshold

I'm starting learning about clustering so perhaps this is a basic question. The idea is to generate clusters out of an array of floats, 1 dimension and N dimensions, get the mean value of each ...
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1answer
154 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 ...
3
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1answer
180 views

Using PC scores or cluster analsis in predictions

I have very big data and low number of observations. So I decided to use PCA to reduce dimension of the data. The following is R example (just an dummy example - for workout): ...
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19 views

clustering versus projection - what are the best example/scenario to explain their differences

I am dealing with non statistician who know are crunching data but don't have a deep understanding of statistics. I am trying to introduce them to non-matrix factorization methods but it has been ...
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2answers
34 views

Clustering of accelerometer events

Refer to the images below. I have an accelerometer attached to a door that logs events everytime someone opens and closes a door. I'm attempting to predict the individual who opened or closed the ...
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1answer
65 views

Rescaling exponentially distributed variables before clustering?

I want to cluster data that contains binary variables, exponentially distributed (power law) variables, and normally distributed variables. I'm considering preprocessing the data in the following way ...
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1answer
33 views

Similarity between different length vectors containing related items

I have a vector (V1) with which I need to calculate the similarity of other vectors (ex V2,V3 ... ) which may be of different lengths. The different angle here is that the elements inside the vectors ...
2
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1answer
28 views

Gaussian clusters and original distributions

In Gaussian clustering (i.e. General Mixture Models) we model the data with some clusters. For example, in the below figure, we have two clusters $C_1, C_2$, each of which are modeled with a Gaussian ...
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2answers
90 views

Segmentation using cluster analysis in SPSS

I am doing a segmentation project and am struggling with cluster analysis in spss right now. Could you please help me get this answered: How do I determine the quality of the clustering in spss? In ...
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0answers
19 views

Number of variables when using Self-Organizing Map

I have a dataset containing $p$ variables (or columns) denoted by $X_i$ for $i=1,...,p$. I am trying to cluster this dataset using Self-Organizing Map. There are 3 main variables within these $p$ ...
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0answers
22 views

ML Bank transactions assignement to invoices

In a effort to reduce human intervention, I'm trying to optimize the process of assigning bank transactions to invoices. This task should be done once every year, so we can assume our dataset won't ...
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0answers
55 views

How to cluster with binary, nominal, ordinal and continuous variables?

I am using SAS to do clustering analysis on a huge dataset. Since my dataset contains various types of variables, I am confused about the appropriate method to perform the analysis. Here are my ...
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1answer
44 views

The representation of a high-dimensional data set by a low number of data points

I know that some of the questions I am asking here have been answered in a general case in the two questions I am referring to in the problem section. Nonetheless, I am asking for a very specific case ...
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1answer
69 views

Approximating a Complementary Cumulative Distribution Function via a piece-wise function

I hope this is not too much to read, but I tried to give you a specific overview over my problem. I am currently trying to model the German electricity market, with a special focus on balancing ...
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2answers
42 views

How can I get an overview of realtime dataset?

Can I use some part of the real time dataset for getting an overview about the dataset before applying an algorithm? Can I use ELKI or ...
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2answers
108 views

How can I cluster data in a grid-like fashion and heat map the averages in R?

I have a data frame of 3 columns. The first one is the response variable the second and the third ones are some criteria. You can create your own example similar to mine, using this piece of code with ...
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0answers
122 views

Clustering communication patterns to detect multiple identities

I have a data set of communication patterns between chatting agents. Each agent can have multiple profiles or identities. I am interested in developing a way to investigate the similarity between ...
2
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1answer
75 views

Is there a package that I can use in order to get rules for a target outcome in R

For example In this given data set I would like to get the best values of each variable that will yield a pre-set value of "percentage" : for example I need that the value of "percentage" will be ...
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2answers
252 views

K-medoid clustering in python

How do I implement k-medoid clustering algorithms like PAM and CLARA in python 2.7? I am currently using Anaconda, and working with ipython 2.7. I have tried scipy.clusters but they don't seem to ...