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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2answers
55 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 ...
2
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3answers
4k views

How to interpret the dendrogram of a hierarchical cluster analysis

I think I have some idea about hierarchical clustering but there a few subtle questions. I use the R example below: plot( hclust(dist(USArrests), "ave") ) What ...
4
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1answer
173 views

Clustering data that has mixture of continuous and categorical variabes

I have data that represent some aspect of human behavior. I want to cluster it (unsupervised) into behavioral profiles of some sort. now, some of my variables are categorical (with 2 or more ...
2
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1answer
152 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
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1answer
76 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 ...
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2answers
42 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
5 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 ...
2
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1answer
119 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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1answer
14 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 ...
0
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1answer
209 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 ...
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0answers
9 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 ...
4
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1answer
68 views
+100

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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0answers
13 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 ...
1
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1answer
90 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. ...
1
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1answer
43 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 ...
4
votes
3answers
114 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 ...
1
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2answers
73 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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0answers
45 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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0answers
18 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
36 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 ...
0
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1answer
710 views

Normalizing Term Frequency for document clustering

I have a problem understanding the normalization of Term Frequency weight in document Vector Space Model for clustering. Let's say that for document d I have counted occurences of all terms. I ...
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0answers
22 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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1answer
122 views

How to generate new Topic for new documents?

what approach would help me generate new topics for new documents? I read this page in order to learn more about the effect of specifying keywords for the topics that we care about detecting in new ...
3
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2answers
93 views

Latent Class Analysis vs. Cluster Analysis - differences in inferences?

What are the differences in inferences that can be made from a latent class analysis (LCA) versus a cluster analysis? Is it correct that a LCA assumes an underlying latent variable that gives rise to ...
0
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1answer
24 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 ...
0
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1answer
25 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 ...
3
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1answer
71 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 ...
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0answers
11 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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1answer
148 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 ...
6
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2answers
295 views

Does a distance have to be a “metric” for an hierarchical clustering to be valid on it?

Let us say that we define a distance, which is not a metric, between N items. Based on this distance we then use an Agglomerative hierarchical clustering. Can we use each of the known algorithm ...
6
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2answers
293 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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3answers
134 views

Agglomerative Hierarchical Clustering “complete linkage” as opposed to “single linkage” dendrogram

Will any dataset clustered via each of the following methods: Agglomerative Hierarchical Clustering using "complete linkage" method Agglomerative Hierarchical Clustering using "single linkage" ...
2
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1answer
213 views

Hierarchical clustering: is it possible to combine single-linkage clustering and average linkage clustering?

A "seismic section" shows amplitude for m discrete x values along its horizontal axis times n discrete time values along its vertical axis: Peaks in amplitude (black) are centered on horizons; ...
1
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1answer
77 views

Motivations for Shi-Malik Algorithm

So I've been trying to make sense of the clustering algorithm on page 6 of this paper. Are the "first" k eigenvalues they refer to the smallest eigenvalues? What are the $y_i$ exactly? I don't ...
5
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1answer
114 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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2answers
360 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. ...
0
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2answers
93 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 ...
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0answers
26 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 ...
2
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2answers
118 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 ...
3
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0answers
35 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 ...
0
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0answers
13 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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0answers
8 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 ...
2
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2answers
180 views

Understanding and Implementing a Dirichlet Process model

I am trying to implement and learn a Dirichlet Process to cluster my data (or as machine learning people speak, estimate the density). I read a lot of paper in the topic and sort of got the idea. ...
5
votes
1answer
90 views

Co-occurrence of properties in a population

I have 150 properties that may occur in a population of 10000 people. Individual people may have none, one or a couple of these properties. The properties are not mutually exclusive and have different ...
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0answers
19 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 ...
2
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2answers
123 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. ...
2
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1answer
207 views

PAM with Gower distance matrix

My data is is mostly continuous but has one binary variable. I tried the pam algorithm in R with the Gower index, but the number of clusters that give the best ...
0
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0answers
15 views

Logistic regression and cluster ID

The dataset consists of all prescriptions classified as on or off-label (0 or 1), meaning possible more than one prescription per child (pnr-number) I want to know the off-label rates per year for ...
1
vote
1answer
31 views

Hierarchical clustering: different result when I change labels

I am running hierarchical clustering with a distance matrix M_norm: hc <- hclust(M_norm^2, method = "ward.D") plot(hc, cex = 1, hang = -1) When I use ...
3
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1answer
155 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 ...