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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Non parametric clustering by discretizing continuous IV

My final target is to develop a predictive model for a rate(fraction) DV. The DV showed bimodality and I have no variable that seperates the two modes. Hence I created an IV using two observed IVs ...
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1answer
213 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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42 views

Kmeans plotting on discriminant coordinates

When you plot a kmeans model (in R) with the plotcluster() function, it plots the clusters against the axis of the 1st and 2nd discriminant components (dc). In reading about these axis- some state ...
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17 views

Structural Stability of Hierarchical Clustering

I am interested in some papers and reports about analysing the following problem: Assume, we have a stream of objects and a defined similarity/distance measure to calculate similarity/distance between ...
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60 views
+50

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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2answers
34 views

Does clustering need scalar data?

I am trying to cluster 43,000 individuals on about 50 variables. The data contained in the variables are minutes of a radio shows which people listened to in the range of 0 - 3,000,000 minutes. My ...
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1answer
225 views

Pull out most important variables from PCA

I would like to get the most important variables from a PCA result. I see two clusters in the plot. I now that is possible that there is no only one variable causing this, so maybe I would have to get ...
2
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1answer
17 views

Using an asymmetric distance matrix for clustering

I'm implementing a clustering task over a precomputed distance matrix. There are several distances I can use for the pair-wise distance matrix, some of them are not a metric (not symmetric). Can ...
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26 views

How to compare and cluster sets of daily time series?

I have multiple dataframes each representing traffic speed for each day of the year (366 dataframes for 366 days of the year). The raws of the dataframe are timestamp from 00:00 to 23:55 at 5 minute ...
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1answer
17 views

Clustering Consumer data with over 100 variables and 50000 rows each

I am tasked with performing a clustering exercise for a consumer survey dataset with the hopes of finding distinct consumer segments. In the past, I've done it using a variety of techniques- ...
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15 views

Problem on clustering

I have around 45 variables in a dataset of 500,000 rows. When I look at my variables, only 10 of them are quantitative - policy premium, age etc. and rest 35 are categorical - State, Smoker/Non ...
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1answer
358 views

Clustering text with python

I asked on stackoverflow but they suggest me to move here for better answers. I copy paste the question. I decide to play a little with similarities and clustering text. I have already create the ...
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10 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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19 views

Finding patterns in individual behaviour [closed]

I have a data set of 3000 individuals and 5 measures, which measure individual behavior (M=3000x5). I would like to find patterns present in this data set, for example common behavior organisation ...
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3answers
154 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 ...
2
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1answer
9 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 ...
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1answer
94 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. ...
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0answers
11 views

Design effect in Cluster Sampling [on hold]

I am facing a problem in calculating sample size of survey. When I am adding design effect this in calculation than sample size become increased. Why design effect in important for calculating sample ...
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3answers
120 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 ...
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2answers
4k 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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2answers
108 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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1answer
2k views

Gower's dissimilarity index

I would like to ask a question about Gower similarity/dissimilarity index. Is it ok to use the Gower dissimilarity measure with Ward linkage clustering? I was reading that the Gower similarity index ...
4
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3answers
207 views

How to figure out what numbers often appear together in a dataset?

I have a lottery style dataset we produce internally (example below). I am trying to figure out which numbers appear most frequently together. Example questions: What are the top 10 pair of numbers ...
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1answer
28 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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1answer
163 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 ...
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1answer
21 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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1answer
29 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
176 views

Quantitative results of clustering analysis

Currently, I am doing a clustering analysis for two sets of data. One smaller dataset (about 100 data) got ground truth labels, and one larger dataset (about 2000 data) has no ground truth labels. ...
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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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32 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 ...
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0answers
12 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 ...
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2answers
75 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 ...
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2answers
102 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 ...
3
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2answers
110 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 ...
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1answer
125 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 ...
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1answer
39 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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2answers
378 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. ...
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1answer
18 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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0answers
9 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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0answers
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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3answers
1k views

What is the difference between Multiclass and Multilabel Problem

Can any one let me know know the difference between Multiclass problem and Multilabel problem.
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1answer
476 views

What is the intuition behind the variation of information (VI) metric for cluster validation?

For non-statisticians like me, it is very difficult to capture the idea of VI metric (variation of information) even after reading the relevant paper by Marina ...
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1answer
221 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 ...
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2answers
119 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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1answer
91 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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2answers
3k views

Is there an R function that will compute the cosine dissimilarity matrix?

I would like to make a heatmap with row clustering based on cosine distances. I'm using R and heatmap.2() for making the figure. I can see that there's a ...
0
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2answers
46 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 ...
5
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1answer
682 views

How do I algorithmically determine values of T1 & T2 for canopy clustering?

I am trying to use canopy clustering to provide initial clusters for KMeans in mahout. Is there a way to determine / approximate the values of the distance thresholds T1 & T2 algorithmically? ...
2
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2answers
125 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. ...
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1answer
28 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 ...