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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21 views

How is Weka calculating nominal attributes for K-means clustering?

I have both numeric and nominal variables in my dataset. Before applying clustering in Weka, I specified nominal variables to Weka and select K-means clustering. It is good that my nominal data seems ...
-2
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0answers
22 views

What to do after calculating Gower for clustering? [on hold]

I used daisy function with Gower metric and found a matrix in R. What is next step for clustering?
2
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1answer
31 views

How does the Gower distance calculate the difference between binary variables'?

I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. ...
0
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0answers
18 views

Selecting the right BIC value

I'm using the hddc for an assignment to find the optimal number of clusters. The dataset is 9-dimensional and consists of 200.000 rows, however, the BIC values that I'm getting are really high. How ...
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0answers
27 views

Inter-cluster variance

Can you please help me understand how is inter-cluster (between clusters) variance defined? As opposed to intra-cluster variance which is pretty straightforward, I have not managed to found a clear ...
0
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1answer
44 views

How to visualize cluster data in a scatter way

Having a clustered dataset, I want to visualize a scatter plot for two fields so every cluster is shown on the plane by its mean value (also good to have a radius equal to std). How does one do this ...
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1answer
41 views

k-means cluster, How to re-calculate centroid when using cosine similarity?

I have a requirement using k-means cluster method with cosine similarity instead of Euclidean distance. for example: ...
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0answers
19 views

Validating feature patterns of subgroups in clustering

I am trying to identify the typical developmental trajectories that participants follow in a learning task. The data set includes the performance of 1,000 learners over 10 trials each and, say, looks ...
2
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1answer
35 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
12 views

How to count overall similarity? [closed]

What I want to do is calculate the overall similarity. How can I do that?. For example, I have this clusters with the number of the cluster member, how can I calculate the overall similarity? ...
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1answer
17 views

What is the easiest way to evaluate k-means clustering?

I did clustering with k-means, but I haven't complete my project, now I have to evaluate the result of the k-means clustering, and I want to do that with the easiest way. does anyone have any ...
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1answer
49 views

Cluster interpretation

I'm running flat clustering algorithm on my dataset that contains numeric (not categorical) data. Is there a method that can give me interpretation of clusters, and emphasize what are the most ...
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1answer
23 views

How to map clustering results to known groups?

I have a data set, which form 3 known groups. I performed k-means clustering algorithm on the data set, setting the number of clusters to be 3 as well. I end up with 3 groups by k-means. Wishing to ...
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0answers
15 views

Cluster analysis (not centroid-based, fuzzy, Matlab)

could you please help me find a cluster analysis algorithm that has the following properties: can deal with "entangled" data ...
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1answer
39 views

Best clustering technique for outlier detection?

I have around 15-20 points every second, and I would like to detect outliers based on -their density along x-axis , that means if I am using k-mean clustering then I specify that in x-direction max ...
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0answers
26 views

KNN - does it use centroids?

I'm really confused now having read so many articles on KNN, I can't help but think I'm missing the obvious. Let's say I have persons P1 and P2, P3 are represented with attributes of height, weight ...
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2answers
70 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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1answer
17 views

Matrix reordering algorithms

I have a similarity matrix and I would like to apply an algorithm that reorders the entries based on their similarity. The aim is to move entries with high similarity closer to the main diagonal. The ...
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1answer
34 views

Clustering based anomaly detection

I'm trying to implement anomaly detection based on clustering. I'm hopping for confirmation of my approach, and I'm exposing my idea, being aware that I could have miss something in my analysis, so ...
1
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1answer
30 views

Tool form Hierarchical clustering

I'm trying to perform a hierarchical Clustering Analysis in a dataset of 40 attributes and +70,000 records, which is mostly composed by categorical variables. I've used Matlab and RapidMiner to ...
6
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1answer
154 views

How is this “United States of Reddit” graph created?

Below is a graph from p. 202 of Christian Rudder's Dataclysm, though it was made by James Dowdell. It illustrates the relationships betweens various top 200 subreddits, which are areas of interest on ...
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25 views

Top K variable that represent entire dataset

There are 100 variables in the dataset. Also, i have extracted some additional information about each variable viz Var1 is correlated (Pearson correlation) to Var21,Var25,Var34,Var45,Var55 ; Var2 is ...
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0answers
5 views

Hand Coordinates Clustering for vector quantization

I've a sequence of pitch, yaw, roll of the hand, plus pitch and yaw of the fingers. So i got a 13-dimensional vector. Which is the best way to understand how to cluster these data in order to perform ...
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0answers
26 views

Correlation space as preprocess to hierarchical clustering

Say you have data matrix X of size NxP where N is the number of samples and ...
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0answers
61 views

Replicability of Cluster Analysis Solutions / Does Cluster Solution Order Matter

I am performing cluster analysis on a sample (psychology) and I would like to determine how to check the replicability of the cluster solutions. More specifically, I am following the protocol laid out ...
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9 views

Discovering dis-associations between periods of time-series

I'm interested in discovering some kind of dis-associations between the periods of a time series based on its data e.g. find some (unknown number of) periods where the data is not similar with the ...
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0answers
35 views

Two step cluster analysis and a binary matching coefficient

I want to commence a two-step cluster analysis, since the database I am conducting analysis on contains important metric as well as nominal values. => Question #1: Should the binary and the metric ...
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1answer
56 views

Determining number of clusters K-means [duplicate]

I would like to automatically determine the number of clusters for K-means. I have read that elbow method could be used for that. The thing that confuses me is - I have to rerun algorithm while ...
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1answer
19 views

Clustering objects based on event timestamps

I have data for $n \approx 500$ objects, and for each observation I have between ~50 and ~200 observations. Each observation consists primarily of a timestamp when an event happened (and includes some ...
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0answers
9 views

Mean of vectors minimizes L2-norm [duplicate]

Recently introduced to data mining and am trying to understand how the mean of vectors minimizes L2-Norm/Euclidean distance. I've tried googling it and can't seem to find a proof as to how something ...
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0answers
15 views

R Clustering Evaluation (Adaptive Kmeans)

i know there are several threads about this topic, but most i read, most i get confused. I'm doing a project that consists in clustering some data (news articles). I used adaptive Kmeans ...
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0answers
19 views

Two-step cluster analysis and autoclustering statistics

In older versions of SPSS there was displayed an auto-clustering statistics table with e.g. BIC criterion and its change for various cluster solutions. In later versions of SPSS (e.g. 21) I do not see ...
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1answer
39 views

How to compute the centroid of a cluster for Gower distances

I'd like to assess how scattered a cluster of binary vectors $X_j$ is, and as I understand the conventional way for doing this is: $$ S = \frac{1}{T} \sum_{j}^{T}\|X_j-A_j\|_p, $$ where $A_j$ is the ...
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0answers
31 views

What is the next step after acquiring the parameters(means, covar, priors) from GMM via EM

I am comparing the results achieved from clustering via K-means and GMM. For comparison I have accumulated a dataset of images. The training set consists of 359 images. I used SIFT to extract the ...
2
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1answer
63 views

Semi-supervised clustering high-dimensional data

I have a data set with 20% labelled samples and 80% unlabelled samples. I have $C$ classes. More than $C$ classes may exist in the data. Each sample is a $70$-dim vector. The size of the dataset is N. ...
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1answer
94 views

Hierarchical or Two-step cluster analysis for binary data?

(This question is an edited version of a question I previously posted which one user recommended would benefit from more focus). I have 2000 questionnaires from respondents which ask 33 different ...
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17 views

Cluster analysis of binary data [duplicate]

I have 2000 questionnaires from respondents which ask 33 different questions about which issues are present in their lives - i.e. alcohol abuse, domestic violence, mental health, child abuse, learning ...
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1answer
18 views

Affinity propagation comments

I was looking into affinity propagation for my similarity matrix problem and thought it would fit well. However, browsing literature I found this comment that basically breaks both legs of affinity ...
2
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1answer
36 views

recommendations for test data set(s) known to have well separated clusters [closed]

I am working on visualizing clusters in high dimensional space. I have had good luck with "real" data sets contributed to the UCI Machine Learning repository. Unfortunately, none of these data sets ...
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0answers
27 views

Difference between Weighted Average Entropy and Adjusted Mutual Information (for evaluating Clustering)

I was advised by my team leader to use this weighted average entropy to evaluating the performance of my dbscan clustering algorithm, and its mathematical formulation is: Scikit provides what many ...
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2answers
38 views

Suitabiility of the confidence score generated by SVM as a proxy for membership function

SVMs can generate a confidence score which is basically like a probability for a particular data item to belong to the particular class. I want to use this probability as a proxy for the 'distance' of ...
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0answers
14 views

How to split a class which is not very cohesive?

Using the silhouette width metric I can find out as to how well each object lies within its class after classification is done. I next find the average silhouette width of objects within a class and ...
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0answers
29 views

Average within-cluster distance using divisive clustering

I have to prove that the average within-cluster distance for 10 data points cannot increase when going from 1 cluster to 2 clusters (divisive clustering). Intuitively, it seems obvious that this is ...
2
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2answers
53 views

Understanding differences between large and small dimensional data when implementing algorithms

I'm working on a local outlier factor implementation based on the wikipedia entry : http://en.wikipedia.org/wiki/Local_outlier_factor This article seems to explain it in just two dimensional data. ...
0
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1answer
50 views

Analysing ranked data

I had following question in my questionnaire: Rank following factors: price, quality, advertisement, brand, reference from 1 (very important) to 5 (least important) that influenced on your buying ...
0
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1answer
20 views

which distance should be used with UPGMA clustering

I am trying to cluster a biological population on the basis of morphological characters using UPGMA clustering method, but I am not sure which distance should I use- Mahalanobis or Euclidean. What are ...
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0answers
22 views

How can you cluster a set of functions with unknown functional forms?

Say you've $N$ functions $f_N(x)$ defined on a regular grid $x$. You don't know the form of $f(x)$, you've only got several realizations of it. The different functions are related to each other ...
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0answers
18 views

Clustering with Restricted Boltzmann Machine

I am working with the basic RBM that can be found on Geoffrey Hinton's webseite and the MNIST dataset. What I want to do is graphically cluster the input data. I am working with a three layer network ...
0
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1answer
14 views

Cluster analysis for multi-response question

Let's say I have check-all-that-apply survey question. What kind of analysis can I run to understand if there are meaningful clusters (i.e. there's a cluster of people who choose A, B, C, and another ...
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0answers
14 views

Grouping search queries by similarity of search results

we run some studies using google search queries. We need to cluster these queries in topics and we would like to find some unsupervised approach. for each query we have the search results. I ...