Cluster analysis is the task of 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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clustering evaluation for a special case

In my dataset each point comes from one of 3 classes, so the true labels are like [0,1,0,0,0,2,1....]. I have to cluster them in 200 clusters. I want each cluster ...
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32 views

Cluster analysis of large, multiple answer dataset

I have to analyse data from a marketing study. I will use SPSS. The questionnaire will look like this: Q: Imagine Situation X. Select 1-3 Criteria from the list that best describe your feeling. ...
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28 views

Interpreting Silhouette plot

Can someone help me interpret this silhouette plot? The things that come up on my mind are: Some clusters are very small Orange cluster is very big Pink, dark green and light green clusters are ...
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2answers
104 views

How to calculate distance between points in DBSCAN matrix data? [closed]

I'm making a simple C implementation of DBSCAN following his pseudocode. If I well underand how DBSCAN works, I may represent my set of N elements (each with M features) with a NxM matrix. When it ...
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14 views

How to detect how clustered coordinates are in a graph? [closed]

Assuming we have a 2D graph with n points, I want to detect how clustered are the points. By clustered I don't mean only how close they are in general, but a very clustered graph can be one with m ...
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10 views

Clustering correlated variables

I have a dataset with 10 variables. Three pairs of these variables are correlated. What happens if I add all of these variables in the clustering? Does this depend on the type of clustering? I found ...
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1answer
35 views

Grouping usernames/emails in a data set

I have a column in a dataset that is the 'user'. Can look like this: tom green tgreen tomgreen@here.com sam blue samtha green How do i get this to group this so that the first three are grouped ...
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12 views

compare mixture models

In my department there has been a discussion going on whether there is a way to compare clusters derived from mixture modelling in something like goodness of fit or adequacy. after long discussions ...
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13 views

Randomized groups for A/B testing

I have the dataset where the dimension = 10 and number of samples = 20. Let's denote the features by $x_1, x_2, ..., x_{10}$. I'd like to analyze the effect of $x_2$ on $x_1$. I applied the following ...
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1answer
54 views

Proper dataset format for K-Means and DBSCAN clusterers

I'm trying to classify web traffic using clustering algorithms with my own C program, capturing packets with libpcap. In this article K-Means, DBSCAN and AutoClass ...
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11 views

How to compare multiple non-hierarchical classications of the same dataset

I'm a taxonomist working on an identification consistency project in which a couple dozen researchers were asked to manually classify the same set of images into like groups. Each classification will ...
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29 views

Clustering with restrictions

I have this dataset of a ranking of roughly 32.5k players in increasing order. The third column contains the number of players which have the corresponding score, whilst the second is the number ...
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1answer
46 views

What is the probabilistic view on clustering? [closed]

Say that we got a set $\mathcal{X} = \{x_1, x_2, \ldots\}$ of samples. You want to partition $\mathcal{X}$ into $k$ subsets, where $k$ is unknown besides the fact that $k \ge 1$. How clustering ...
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1answer
54 views

Comparing kmeans cluster

I have 150 images, 15 each of 10 different people. So basically I know which image should belong together, if clustered. These images are of 73 dimensions (feature-vector) and I clustered them into ...
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2answers
69 views

What Algorithm to cluster web user sessions without knowing the number of clusters?

I created user sessions from server log data. Based on the URLs I categorized each server request according to the respective page content (e.g. topic_1 = main page, topic_2 = team members, etc.). The ...
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61 views

How would one use KDE as a one 1D clustering method?

I need to cluster a simple univariate data set into a preset number of clusters. Technically it would closer to binning or sorting the data since it is only 1D, but my boss is calling it clustering, ...
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1answer
36 views

When would I use EM instead of k-means?

When would I want to assign cluster probabilities to patterns instead of hard assignments to clusters? Can someone elaborate?
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46 views

Is there a difference between 1D Mean Shift and KDE for clustering 1 d data?

I need to cluster (or group) large one dimensional data sets into a set of fixed bins. I started out using K-means, but I want to look into other approaches. Two that I have found are Mean Shift and ...
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8 views

Can I conduct multilevel analysis with two aggregated data sources?

I have two data sources with completely different specific individuals. One contains individuals answering whether or not they have watched the movie "Lego", and the other date source contains ...
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5 views

Assigning new observations to already created clusters [duplicate]

I have created 6 segments in SPSS using the Two-Step Clustering approach based on about 2600 observations. I have now collected 1000 new observations and would like to be able to assign these new ...
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43 views

Clustering and A/B testing

My question is the following: Let's imagine I've defined clusters in my data (different segments of customers) and I run an A/B test. Can I compare the performances of the different clusters on the ...
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10 views

Cluster Component Coefficient Calculation for data in Rows

I have my data in the form such as: ...
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22 views

Finding cluster overlapping

I've a set of locations and I've clustered them thrice on the basis of some different parameters, now I want to find overlapping of the clusters obtained. So basically the dataset now contains list of ...
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1answer
64 views

Compare clustering results based on intra cluster similarity

I am working on a project for my university. A part of this project is to compare the influence of PCA on clustering. Therefore I have a football player dataset that contains a feature called ...
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1answer
25 views

Estimate group averages

If I have 100 numbers from two separate groups $X$ and $Y$. How can I manually estimate or derive an algorithm to automatically estimate $AVG(X)$ and $AVG(Y)$? I know all the numbers, but I don't ...
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1answer
52 views

Is it necessary to normalize data for hierarchical clustering of mixed variables using complete linkage?

I have a dataset with 3 numerical variables and 1 categorical variable which is binary (0,1). For clustering these data, should I normalize my numerical variables to the unit range (0,1) by ...
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137 views

How does Principal Component Analysis help me understand my data?

I have a dataset which contains 10000 examples. Each example has 100 dimensions. These dimensions have the same scale. I clustered all examples using their 100-dimensional vectors and drew the elbow ...
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59 views

confusion matrix and Jaccard index computation in O(n) for cluster comparison

My problem: I have two clustering (or partitions) of a set of numbers $\{1,...,n\}$, each with $k$ cluster (or subsets), that i have to compare and, to do that, i'd like to try some different indexes ...
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41 views

DBSCAN application for detection of anomalous instants in a particular time series

I have time series/matrix with cpu utilization of 4 servers (about 17k points). I am trying to use DBSCAN algorithm to find out which server is operating suspiciously compared to other using the ...
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1answer
35 views

How do we put various multivariable data in cluster bucket

A data with multivariable of mixed types (Nominal and Continuous) are clustered using R package of Daisy/Agenes. How are we going to put the variables in the cluster bucket I was thinking to put max ...
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3answers
69 views

Is there a situation when one would use L1 norm over L2 norm in k-means algorithm? [duplicate]

Is there a situation when one would use L1 norm over L2 norm in k-means algorithm? In most of the articles online, k-means all deal with l2-norm. L1 norm does not seem to be useful because it is not ...
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1answer
14 views

Unsupervised clustering of households into types

Traditionally, households fall into a couple of discrete categories. For example: Husband and wife Husband, wife and young kids Divorced Wife and kids Bachelor Adult child living with husband and ...
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48 views

Log-likelihood distance

How to calculate log-likelihood distance between clusters in two step clustering? if the following is the solution,then how to proceed? I would appreciate if someone can help me to find this. I am ...
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62 views

What should be the ideal number of clusters for the plot whose image is given?

I have a dataset whose wssplot I've created but then not able to find any sharp elbow, so if anyone could please me with it?
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36 views

How can I simulate feature tolerances in DBSCAN to see how the clusters change?

I am performing clustering based on the DBSCAN algorithm on a 3-dimensional data set. After running the algorithm, I get X clusters as a result. What I want to do is to see how the clusters behave if ...
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53 views

What is the use of distance matrix in clustering algorithms?

I found a C library for clustering and I was reading about the distance matrix here: it says: The first step in clustering problems is usually to calculate the distance matrix. This matrix ...
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29 views

Exploring distribution of pairwise distances before clustering

I'm trying to perform clustering on a 200+ feature dataset consisting of brain measures for 200 healthy controls and 200 schizophrenia patients. However, I have the feeling the data points do not ...
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17 views

K-means on categorical and numeric data [duplicate]

I've seen people use K-means on mixed categorical and numeric data before, however I'm not sure this should be done. Additionally, I've read on this forum that this shouldn't be done. Folks have ...
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How to find similar kind of project specification using Clustering Algorithm?

I have budget estimation of some bio-medical projects and their specification details. Could any one suggest me how to do clustering algorithm to find the similar kind of specification. Which ...
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1answer
39 views

Clustering patients according to biomarkers: an easy way out?

I've just started reading about clustering and classification. It's a djungle, a fascinating one. Currently, however I have a rather urgent task, i.e to perform a sort of cluster analysis in the sense ...
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2answers
29 views

Cluster two feature samples with no knowledge of the number of clusters

Thanks in advance for the help I have around 13000 samples with two features each and I would like to cluster these samples into groups. A few caveats. One, I don't know how many groups there are ...
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1answer
64 views

Using Ward's method for clustering and Dice's similarity coefficient for binary data

Is it valid to use Ward's method for clustering and measure similarly by Dice's coefficient for binary data? I am trying to isolate the most similar groups from a set of binary variables while ...
0
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1answer
41 views

Grouping 1D data to find intervals with most data points [duplicate]

I have a sorted list of integers. From this list, I would like to find intervals of numbers in which most of the numbers are concentrated. I have used K-Means with R and played around with the k ...
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14 views

Optimal grouping in one dimensional data with constraints [duplicate]

I have a 1d series of data with of approximately 100 values. I would like to partition series into 1, 2 or 3 groups, depending on the proximity of the values. What statistical technique would work ...
0
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1answer
18 views

Evaluating a clustering against multilabels

I have a clustering of text documents, where each document is uniquely assigned to a cluster. I have a set of labels (keywords) attached to each document. That is, each label may be applied to many ...
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22 views

Clustered Data and Kruskal–Wallis

I have a data set of loan amounts that is naturally clustered into 3 groups: 0 - 5 year loan 10 - 15 year loan 20 - 30 year loan The 3 groups are not normally distributed. Since I don't need to ...
3
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1answer
39 views

Under what conditions would clustering on top of Principal Components would return different result (and worse) than clustering on the data itself?

Since Principal components capture most of the information, clustering on them should provide similar result as that of the clustering on the original data. As such, it seems to me (who's not a ...
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29 views

When is preferred the relative and stability-based cluster validation?

I need to validate a clustering algorithm result. I know that Cluster Validation is commonly divided into four categories: internal, external, relative and Stability-based criteria, where internal and ...
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28 views

“Pairwise dependence probability”

From pg 9 of [1]: The notion of dependence between two variables A and B is taken to be mutual information; the amount of evidence for dependence is then the probability that the mutual ...
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57 views

R: finding spatial patterns in rasters (Moran's I etc)

i'm not really experienced in spatial stats yet, but i'm growing into it. I basically want to ascertain if certain values in a raster are a) autocorrelated and b) are more likely to exist in a ...