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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15 views

clustering verifying two basic invariance properties

disclaimer: I already asked something similar on stack overflow, but it seems to be a better place for that question here. I recently became interested in axiomatic definitions of clustering, cf. ...
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1answer
22 views

Can I use HCA-Ward's cluster-centers to run a K-means including a new item, to see to which cluster is more similar to?

Thank you for reading my question. I have an archaeological case-study, that we can call "Site1", that I want to compare with 9 others "Sites" studied by other scholars. For all of them I have 8 ...
2
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2answers
224 views

Analysis of hierarchical clustered hospital data

I am hoping to get some advice from this excellent community on how I might try to proceed with an analysis of patient outcomes for a large conglomerate of hospitals. Essentially the dataset that I ...
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1answer
40 views

Determining characteristics of peaks after mclust finite mixture model

I'm working with the mclust package in R (specifically using densityMclust). As output, I have a file with mixing probabilities, variances, and means for each ...
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2answers
41 views

Which K-mean algorithm I have to use for this problem?

Perform a k-means Clustering (non-iterative algorithm) using k=2 randomly initialised centroids (cluster prototypes), and the Euclidean distance. At the moment I manage to understand you can use ...
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1answer
13 views

Separating one group from other samples where the other samples may not belong to the same population

The way I see it, this is somewhat of a modified clustering problem. Let's say I have 1000 samples where the majority all follow the same behavior since they are from the same population. A number of ...
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1answer
22 views

Comparing / quantifying clusters

I have 'n' observations which are classified in two classes: Class A and Class B. The observations are mis-balanced with Class A constituting around 90% of the samples and Class B around 10%. The ...
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19 views

Fuzzy clustering of temporal data with constraints

I am looking for an algorithm to cluster timestamped events using the weighted elapsed time between the events as the only dimension. There are different types of events. There are constraints saying ...
83
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2answers
6k views

How to understand the drawbacks of K-means

K-means is a widely used method in cluster analysis. In my understanding, this method does NOT require ANY assumptions, i.e., give me a data set and a pre-specified number of clusters, k, then I just ...
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38 views

Gower's Distance issue

So, I'm relatively new to using Gower's distance to do cluster analysis. I've done some research on this for a little while and like the fact it can incorporate categorical variables. To get a better ...
0
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1answer
46 views

Learning a classifier to compute distance between points for clustering

I have dataset of items and want to cluster them. However, I don't have a predefined distance function. Does it make sense to learn a classifier that can predict the similarity between any two items? ...
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11 views

Merging linkage results from separate datasets for the purpose of clustering

Suppose I have a dataset P, This dataset is separated into smaller disjoint subsets Q_i. Since the clustering algorithm which has to be applied is space O(n2), the amount of data in P such that it ...
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1answer
23 views

How to detect noisy entries in the data set

I have a data set (entries described by the list of features X1-X7). This data set contains a small percentage of noise. How can I detect those entries that are subject to noise and exclude them from ...
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10 views

Technique to cluster with multiple dimensions

I have a data set which has respondents categorized as Tier 1, Tier 2 and Tier 3 - scores of their preferred genre of content and keywords relating to the genre. What I would like to achieve is to ...
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0answers
9 views

Bisecting K-mediods [duplicate]

Is there an algorithm like Bisecting K-mediods and what would its advantages/weaknesses be? It seems to me that it could be used well in combination of Dynamic Time Warping for clustering time ...
0
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1answer
30 views

Help with cluster analysis. Is this possible? [duplicate]

I'm working with the productivity of various government documents. In my data I have two variables (annual frequency and time of resolution) and each document gets its position in a Cartesian plane ...
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2answers
57 views

Bisecting K-means using Dynamic Time Warping

I'm trying to cluster time series of different length and I came up to an idea to use DTW as a similarity measure, which seems to be adequate, but the thing is, I cannot use it with K-means, since ...
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0answers
86 views

Gower's dissimilarity measure and Ward's clustering method

I have read some topics in this web side that, it is not true to use Gower's dissimilarity matrix for Ward's clustering algorithm. I have mixed type variables, first I had a dissimilarity matrix ...
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31 views

Implementing Hopkins and Cox-Lewis index in R

I was trying to implement some clustering tendency tools in R, namely the Hopkin's index and the Cox–Lewis index. Here is the link at page 901 to show what they are This is what I managed to come up ...
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23 views

Normalizing regressors in logistic space

I have a bunch of sklearn sgd models that have beta coefficients in the logistic space. I want to see if these models cluster ...
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2answers
253 views

Dynamic Time Warping Clustering

What would be the approach to use Dynamic Time Warping to perform clustering of time series? I have read about DTW as a way to find similarity between two time series, while they could be shifted in ...
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1answer
23 views

Exploring multiple semantic clusters of a given set of terms

I have a list of N object categories(e.g. apple, cell-phone, horse, chair, watch). Are there any methods of obtaining various clusters based on attributes of these categories ? For example, one ...
0
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1answer
17 views

K-Means Clustering on Distributed System

Can anyone explain how the k-means clustering algorithm converges on distributed systems? It seems that each node in our hadoop cluster would simply find a local optimum. How do we update across ...
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0answers
58 views

How to use binary variables in K means/Hierarchical clustering in SAS/R?

I need to use binary variables( values 0 & 1) in K means. But K means works with only continuous variables. I know some people still use these binary variables in K means ignoring the fact that k ...
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2answers
44 views

Cluster analysis as a preliminary analysis

I want to produce four groups (high/high, high/low, low/high and low/low) using two continues variables and compare these groups in terms of a few dependent variables. I know that cluster analysis ...
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1answer
29 views

classification of the groups [duplicate]

Let's say I have two variables: height and weight. I want to produce 4 groups: high height/high weight, high height/low weight, low height/ high weight and low height/low weight. I also want to see ...
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4answers
210 views

Are there any non-distance based clustering algorithms?

It seems that for K-means and other related algorithms, clustering is based off calculating distance between points. Is there one that works without it? Thanks!
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2answers
23 views

Revealing structure of clusters in a dataset

I have obtained values for the same parameter in various locations and I want to cluster them (abundance fraction of different minerals in a hyper-spectral image). These fractions have spatial ...
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1answer
42 views

Update Rules in Expectation Maximization

I am emulating a certain PDF behaviour using a function. However, due to divergent improper integral, I don't have a closed form expression for the normalization constant. To get the PDF, I just ...
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2answers
94 views

Mahalanobis distance measure for clustering

Let's say I have a group of clusters. Would you recommend Mahalanobis distance measure for checking if new arrived data belongs to existing clusters or it is an outlier? Also, would you recommend ...
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2answers
58 views

Use of bootstrap in clustering algorithms

Are there clustering algorithms that take advantage of bootstrap? For example can one combine bootstrap with a standard K-Means algorithm to scale K-Means. I was thinking if the following at a ...
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0answers
12 views

How to segment/profile users after performing classification?

So let's say that you've used logistic regression with demographic factors to make prediction on user bebaviour (e.g. those who clicked on a particular link v those who didn't) and you are satisfied ...
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11 views

Conjoint analysis

I am planning to conduct a conjoint study, but am having problems in terms of the number of product profiles to include. I will have to interview respondents in the markets and hence wanted that the ...
0
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1answer
18 views

Benchmarking hard clustering results against soft clustering results (ground truth)?

Well, I don't have labels (ground truth) for my data points. However, by domain knowledge, I am certain that a particular soft clustering algorithm will produce satisfactory results. Hence, I may use ...
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2answers
84 views

Mutual information for two soft clustering results?

I understand that mutual information (MI) of two distributions $X$ and $Y$ is defined as In the case of clustering analysis, say we are looking for two clusters out of 3 data points. We have two ...
4
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1answer
97 views

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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1answer
76 views

Anomaly detection: multivariate Gaussian distribution

I am trying to do anomaly detection on a heterogeneous dataset (There are unknown groups present in the dataset). I want to try multivariate Gaussian distribution based approach, but I was thinking of ...
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0answers
53 views

Find the radius of a cluster, given that its center is the average of the centers of two other clusters

I do not know if it is possible to find it, but I am using Kmeans clustering, and I am stuck to the following. In my implementation, I create with two different threads the following clusters: ...
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25 views

Clusters as input for classification

I'm currently performing clustering as a batch job and then in real time I'm assigning new points to cluster whose centroid is closest to new arrived point. The other approach that I see is to ...
3
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1answer
57 views

Best clustering algorithm for real estate data

I want to cluster real estate data to determine average price patterns in city and rural regions. My data set contains size, number of dorms, bathrooms and coordinates of the properties. Which would ...
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0answers
23 views

Which kind of analysis could be made to associate a set of genes to clinical values?

I have a set of 5 genes that can be mutated or not, so therefore are intended as dichotomous yes/no vars. I want to identify the effect of the mutation of this genes on a continuous response var. The ...
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0answers
12 views

Profiling high-scoring clusters in a multi-dimensional feature space

I have a large amount of samples, which have a multi-imensional feature vector associated with them. Each sample has a "score", and the length of the feature vector is substantial (n>100, and in ...
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31 views

Investigate correlation between one variable and combinations of others

We're conducting a study which correlate the incidence of various conditions during pregnancy and in newborns and the use of artificial reproduction technique (ART). This way we saw that some ...
5
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1answer
151 views

Clustering data into bins of variable sizes

I'd like to build a model (in R or excel) that takes in large amount of linear data and segments it into "bins". The linear data is an attribute that reflects what condition that section/record is at. ...
3
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0answers
46 views

Use of Hidden Markov Models for Clustering

I would like to ask whether Hidden Markov Models can be used for clustering and if so, in what cases. I have found somewhere, references like this but practically I haven't found a way to do this. Is ...
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16 views

Automatically classifying user activity/sessions on a website?

X-posted from Stack Overflow: I have a large body of records pertaining to user activity on a website. What I want to do is some sort of classification on each user as they navigate my website. Every ...
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13 views

Good mean shift clustering datasets

I am working on a modification of the Mean Shift algorithm and would like to validate my clustering results. I am struggling to find suitable clustering datasets to compare performance with. I'm ...
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0answers
49 views

Observation/case weighting in cluster analysis

Sampling weights, the inverse probability of a unit's selection into the sample, and other more complex and adjusted weights are very often used in the social sciences. There is statistical software ...
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1answer
28 views

What Grouping Method To Determine Average Over Lifetime?

I have the following data: When individual 'x' joined a company. As the data is limited to 2 years I do not know the start date of every individual. When individual 'x' left the same company. If this ...
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1answer
32 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 ...