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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19 views
Curve based clustering of multivariate data (time series like data) [duplicate]
Possible Duplicate:
Reducing no of variables subsetted based on depth for PCA
I have a question, I am trying to apply a method to my research area, which has not been aplied yet, based on ...
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0answers
43 views
Sparse estimated data recommender system
Premise:
For a product and a user, the system has to recommend him/her other non-users related with him/her that are most likely to be interested in that same product.
Available data includes:
...
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1answer
55 views
Shape analysis of an object to create features for pattern recognition
I am currently with a medical imaging project. Just wondering how to measure the shape of a sphere. For example, how to give a measurement that an object is more like a sphere than the other?
I know ...
1
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1answer
97 views
Reducing no of variables subsetted based on depth for PCA
First of all, sorry for the strange title, I had no idea how to describe my problem better.
My issue is the following, I think it is pretty much limited to geosciences.
I have several properties for ...
2
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2answers
58 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 ...
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0answers
24 views
Analysis of Systematic differences in two multifactor pricing models
I am trying to compare two different pricing models for a product. The two models take the same inputs ( 10-12 different factors)and i know the definitions of both functions which calculate the price. ...
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1answer
94 views
Mahout Scability
Do you know any real world examples of how much Mahout can scale? I wonder how much it can scale in collaborative filtering, clustering, and classification ?
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1answer
33 views
Clustering with the same number of objects per group
How can I cluster while forcing the final clusters to have more or less the same number of objects?
I have just tried kmeans in R, and it does not take this into ...
2
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2answers
55 views
Issues with tritomising and dichotomising variable
I see that the issue of splitting a variable into two categories has been discussed on this forum and I understand pros, cons as well as some ways of performing it. The issue that I am interested and ...
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2answers
114 views
In non-negative matrix factorization, does the first N eigenvector have N greatest variance?
I know for PCA, it's true that the first N eigenvectors have N greatest variance.
But I'm not sure whether that's also true for NMF(Non-negative Matrix Factorization). For example, this ...
3
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1answer
155 views
How to explain the connection between SVD and clustering?
Is there an intuitive explanation for how SVD is related to co-clustering when performing SVD on a covariance matrix?
(i.e. the SVD is performed on the matrix $E[X Y^{\top}]$ where $X \in ...
3
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2answers
151 views
How to define a posterior probability of y given x when the model is not probabilistic?
Suppose we have a very simple online k-means where each new data-point is assigned to its nearest center (the mean is updated incrementally). Each center (cluster) is labelled with the most common ...
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0answers
16 views
Comparing sample profiles
I have some samples that have been treated with various chemical agents. Users score the treatment effect using categorical values/bins (i.e < 1, 2.5, 8, ... > 100). Within a range of say 1-100 ...
3
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2answers
196 views
Classification on principal components
For my research I am doing classification on the dataset of three variables.
I run unsupervised clustering (based on a histogram peak technique of cluster analysis)and the result I evaluated visually ...
2
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2answers
114 views
Choosing which data-point to label (active learning)
For an online unsupervised learning algorithm, data-points are learned sequentially. The performance may improve if in addition to the unlabelled data we have some labelled data-points (i.e. ...
5
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2answers
189 views
Calculating similarity and clustering question
I have a dataset of about a million companies containing their names, total employees and annual sales. I want to come up with a function that when given the company returns the 5 most similar ...
2
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0answers
189 views
How to cluster standard errors (by country) using SPSS?
I'm trying to obtain robust standard errors as my regression residuals seem to be correlated... My sample data has 8 countries and I would like to cluster the standard errors by these 8 countries ...
3
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3answers
216 views
How to decide whether to reuse old code or reinvent the wheel?
For a long time now, I have been thinking about working with neural networks and genetic algorithms. I have never been able to decide whether it makes sense to start writing my own code, or to reuse ...
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1answer
92 views
bag of words in an online configuration, for classification / clustering
I have a set of image documents. I extract text keywords from this images using OCR to represent each image as a bag of words (a vector where each value is the number of occurrence of a word in the ...
2
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1answer
51 views
Which metric use for problem of clustering spatial data of wind direction and speed?
I have two dimensional spatial (x,y - coordinates of meteo stations) data for small region (so I could neglect the shape of earth globe), for each (x,y) I have one observation of wind direction and ...
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2answers
42 views
Good Analytical Approach for a problem
I'm trying to figure out what kind of analysis will give me the results I'm looking for.
I have 4 shops and I'm trying to understand what is the typical (most likely) customer characteristics of ...
1
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0answers
32 views
Clustering with constraint size
I want a clustering method which can let me apply constraints on the maximum and the minimum cluster sizes which I can implement. Otherwise suggestions for a combination of existing techniques which I ...
4
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2answers
178 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, ...
2
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1answer
98 views
Spatial Clustering with the constraint that All Clusters have Equal Count
I wish to perform a spatial clustering of scattered data that represents geographic locations of individuals in an urban area. Hierarchical clustering seems to work well, and I have successfully done ...
1
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1answer
172 views
Density calculation in K Means clustering
With the K Clusters generated using K Means Clustering, how do we calculate the density of each cluster? Is there any formula for it?
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2answers
232 views
Does the sign of the adjusted residuals matter in a crosstable?
In a cross table, if the adjusted residual value for a cell is less than -1.96 or greater than 1.96 then we could say that this cell is determinant in the dependency (suppose pearson is 0.03). ...
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3answers
202 views
Clustering with 3 attributes
Please bear with me because I am very new to data mining.
I have a database of 3 attributes: latitude, longitude and temperature. I want to find clusters for the temperature data and I also want to ...
2
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2answers
364 views
Why don't dummy variables have the continuous adjacent category problem in cluster analysis?
I know that if we use categorical variables in cluster analysis we would assume that the scale is continuous and we don't have this concept of distance between two adjacent categories.
But what is the ...
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2answers
41 views
Compute probability of a grouping being correct
I have an exemplar grouping of objects (each with their own feature vector) into categories. I am then given a new grouping of compeltely different objects, and Iw would like to compute the ...
5
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2answers
252 views
Determine different clusters of 1d data from database
I have a database table of data transfers between different nodes. This is a huge database (with nearly 40 million transfers). One of the attributes is the number of bytes (nbytes) transfers which ...
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3answers
100 views
How can I separate each of 100 observations into groups as determined by the data?
I have 3 covariates for 100 observations. How can I separate each of my 100 observations into groups as determined by the data. I was thinking clustering. However, apparently, I need more than 3 ...
7
votes
5answers
238 views
Does preclustering help to build a better predictive model?
For the task of churn modelling I was considering:
Compute k clusters for the data
Build k models for each cluster individually.
The rationale for that is,that there is nothing to prove, that the ...
0
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0answers
292 views
Mahout k-means generates too many clusters [closed]
I am a beginner in Mahout, I use Mahout 0.8 and followed the tutorial in https://cwiki.apache.org/MAHOUT/clustering-of-synthetic-control-data.html
When I use :
...
2
votes
2answers
88 views
Is concept of similarity objective?
Imagine following example:
We have two pairs of points (i.e. 4 objects in some space) and two similarity measures.
According to first similarity measure, objects from first pair are more similar then ...
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1answer
106 views
kMeans - acceptable value for WCSS
Which value for the within-cluster sum of squares points can be accepted regarding a data set of 1000 tuples, 21 attributes (but only 3 are used now)?
I have used Euclidean distance is used, and a ...
1
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1answer
64 views
Distance independent approximation of Nearest Neighbor/k-NN.
Nearest neighbor/k-NN for use with Normalized Compression Distance. I wonder if there exist any approximation of NN/k-NN algorithm which work for all distance measures ? I would like to test ...
1
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1answer
256 views
Clustering of time series
I have a set of almost 1600 time series on 2 years which I want to group into clusters. Do you think this is possible using k-means? Which method do you advice me to use? Is this possible at all using ...
1
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2answers
284 views
Image Clustering with K-means - Postprocessing
I did some clustering on an image (each pixel is an observation that has 5 variables associated with it), I get pretty detailed results but they are a little bit noisey... I think. I used K-means. ...
5
votes
2answers
112 views
How to measure shape of cluster?
I know that this question is not well defined, but some clusters tend to be elliptical or lie in lower dimensional space whilst the other have nonlinear shapes (in 2D or 3D examples).
Is there any ...
3
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3answers
356 views
How to reduce the number of variables in cluster analysis?
I've got 10 (yes, only 10) cases over 1000 variables (e.g. measurements of concentrations of 1000 different compounds at 10 different time points).
I can group these cases into 3 clusters in ...
2
votes
1answer
295 views
What to use, k-means or hierarchical clustering for presence absence data?
I am currently working with a presence-absence database that is mostly zeros (~5% are ones) representing species in space (a species per site matrix). I would like to explore the spatial pattern of ...
2
votes
1answer
121 views
Which are the most effective clustering ensembles?
In supervised learning, there are some ensemble methods that overcome others significantly (adaboost or random forests to mention some).
Few years later, also ensembles in unsupervised learning were ...
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2answers
96 views
Seeking for a fast non parametic clustering algorithm
I'm looking for a fast clustering method to cluster a large kind of datas to a unknown count of clusters.
I know about the PAM-Algorithm. But it's only efficient for low datasets.
Is there a ...
0
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1answer
150 views
Clustering time series with wavelets in R
Can discrete wavelet trasform be used for feature extraction from time series in order to cluster them? Any R code how to do this will be appreciated.
2
votes
2answers
129 views
What function of distance for the questionnaire data?
I have data from questionnaire from school. First question is study program (only 2 programs) and next 35 questions are various questions (influence of friends etc.)
Possible answers for 35 questions ...
-1
votes
1answer
136 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 ...
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0answers
43 views
Blind deconvolution of histogram
I am not sure that this is good forum to ask, but dunno where to ask.
I have a file with histogram data collected from cytometer. The problem is that these data contain several signals and I want to ...
1
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0answers
54 views
How to sum cluster data?
I have a binary variable with probit model, i.e., $P(Y_{ij}=1|X_j)= \Phi(a_i+b_iX_j)$, where $X_j$ is $\mathcal N(0,1)$, and $a_i$ and $b_i$ are regression parameters.
I am wondering what the ...
0
votes
2answers
209 views
Interpret Silhouette plot for large microarray dataset
For a microarray experiment with ~40,000 probes and ~30 samples I used the clara function from R to cluster my expression matrix. How do I interpret this silhouette plot?
Firstly, I don't ...
4
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2answers
104 views
What are features that distinguish clustering, blind signal separation and dimensionality reduction?
In terms of input -> [process] -> output what are features that distinguish clustering, blind signal separation and dimensionality reduction?
From this ...
