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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0answers
24 views

How to find the 1000 closest point to a centroid built from another matrix

I actually work on text-mining. I try to find the 1000 closest documents (inside a corpus of 56000 documents) to a selected corpus of document (150). There are a lot of words in my dictionary. I ...
3
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0answers
30 views
+50

When does pam (partition around medoids) fails to find the optimal solution? (counter example?!)

If I understand correctly, the pam algorithm is a greedy search for a set of medoids such that no other set offers a lower cost (i.e.: the sum of distances of points to their nearest medoid). ...
3
votes
0answers
25 views

Is dimensional reduction using Autoencoders possible with a small sample size?

I have a data set that is not too big but high dimensional, let say 10000 dimensional. I want to use an autoencoder to extract relevant features (clusters) in the data. Usually when I have seen ...
-1
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1answer
20 views

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 ...
1
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0answers
21 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. ...
1
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0answers
14 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 ...
-1
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0answers
10 views

Hierarchical Clustering [closed]

I could use the help of someone of you on the implementation of the Hierarchical clustering algorithm on R from this paper. http://arxiv.org/pdf/cond-mat/0204202.pdf Best, Felix
0
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1answer
33 views

Hierarchical Cluster Analysis: similar to market basket and how to implement in R? [closed]

This is a simple cluster analysis question, but I've not done much clustering at all, so any help would be appreciated. I have N items and there are M people, each picking some of these N items. I ...
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votes
2answers
35 views

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

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 ...
1
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0answers
12 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 ...
0
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0answers
7 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 ...
0
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1answer
28 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 ...
0
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0answers
8 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 ...
0
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0answers
10 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 ...
0
votes
1answer
37 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 ...
0
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0answers
6 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 ...
0
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0answers
22 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 ...
-1
votes
1answer
41 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 ...
0
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0answers
13 views

Fuzzy c-mean clustering (FCM) [migrated]

From these two results for fuzzy c-mean clustering : ...
0
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1answer
25 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 ...
1
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2answers
39 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 ...
1
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0answers
26 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, ...
1
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1answer
27 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?
0
votes
1answer
14 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 ...
0
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0answers
5 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 ...
0
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0answers
4 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 ...
3
votes
1answer
30 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 ...
0
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0answers
7 views

Cluster Component Coefficient Calculation for data in Rows

I have my data in the form such as: ...
0
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0answers
18 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 ...
0
votes
1answer
31 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 ...
0
votes
1answer
23 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 ...
0
votes
1answer
20 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 ...
0
votes
1answer
95 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 ...
0
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0answers
6 views

Understanding the Biclust class in R [migrated]

I'm new in R Language, but I'm using the biclust package for Bicluster Analysis. After to search information in web, I could run some biclustering algorithms but I could not access to the resulting ...
0
votes
1answer
28 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 ...
0
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0answers
20 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 ...
0
votes
1answer
24 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 ...
1
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3answers
49 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 ...
0
votes
1answer
11 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 ...
1
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0answers
19 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 ...
1
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1answer
58 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?
1
vote
1answer
22 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 ...
0
votes
1answer
38 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 ...
1
vote
1answer
18 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 ...
0
votes
0answers
16 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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votes
2answers
23 views

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 ...
3
votes
1answer
35 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 ...
0
votes
2answers
24 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 ...
0
votes
1answer
28 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
votes
1answer
31 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 ...