Tagged Questions

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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20 views

Is there a way to measure overlapping between two clusters? [on hold]

Is there a way to measure overlapping between two clusters that underlie the data? If there is, can any clustering techniques can measure the overlapping? I am not sure I understand it correctly.
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0answers
30 views

Clustering methods for decision trees

My thesis work examines e-commerce data that is clustered using a decision tree, but I am uncertain about where to start. What algorithm or methods does one use to do this?
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2answers
58 views

Why are mixed data a problem for euclidean-based clustering algorithms?

Most classical clustering and dimensionality reduction algorithms (hierarchical clustering, principal component analysis, k-means, self-organizing maps...) are designed specifically for numeric data, ...
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1answer
7 views

Calculating distance comparing sets of frequencies

I have two sets of items, say A (with items a1, a2..) and B (with items b1,b2..). Each item in A appears with different frequency with items in B, so each item would have a list of B items with ...
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1answer
18 views

unsupervised clustering with “unclassified” items

I have data (some behavioral features, measured on some scales) on people. I want to cluster people based on these features. This is an unsupervised scenario, as I have no prior knowledge on the ...
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0answers
24 views

clustering analysis of large amount of time series

I would like to cluster a set of time series, which are composed of around 50000 different time series. Are there established algorithms/package that can handle this scalability problem?
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14 views

Clustering techniques for multivariate data [on hold]

I have a data set like: Var1 Var2 Var3 ... Var M Object 1 Object 1 Object 1 Object 2 Object 3 Object 3 .... Object N I would like to find ...
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1answer
32 views

K-medoids clustering with Gower distance in R

I have both numeric and binary data in my data set with 73 observations. I read a lot about which distance metric and which clustering technique to use especially from this web site. I decided to use ...
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1answer
37 views

Can we use cluster analysis in multiple regression

I am quite new to Data Analytics. I was just wondering whether we can use cluster analysis in Multiple Regression. Let me give you a scenario so that it becomes easier to visualize. I have a dataset ...
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0answers
20 views

What metric can I use to indicate if a class should be split?

I have trained a classifier based on some training data. Now, when I add test data consider the possibility the datapoints do not strongly belong to a class. So much so, that it would make sense to ...
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0answers
5 views

Aggregating Results for pvclust [migrated]

What is the best way to summarize the means or medians of the clusters identified by pvclust? I have done it before with hclust using the cutree command to identify clusters. I have then aggregated ...
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0answers
21 views

(binary) Matrix completion with less known data

Recently, I meet such problems, I call it matrix completion problem. For example, the row denotes the users and the column denotes items. And If one user like the ...
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0answers
27 views

Can I say there would be only 2 groups with such features in this data and prove it using cluster analysis?

I assume that there would be two groups that will emerge within the data with my assumed features. I run cluster analysis and best number of cluster (elbow, dendrogram, etc.) shows it will be 2 and ...
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1answer
22 views

How to cluster data with repeated measurements?

Most clustering algorithms assume that data points in each row are independent. I have some data with repeated measurements from individuals. I can use a standard algorithm, and then check to see if ...
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0answers
13 views

Clustering multi-dimensional data with RapidMiner without knowing k

I am currently struggling to find an appropriate clustering for a data set with binominal label and 10 features (all of them continuous, but in different ranges). As far as handling the high ...
0
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0answers
36 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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1answer
43 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. ...
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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
28 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
45 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 ...
0
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1answer
48 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: ...
0
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0answers
20 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
39 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 ...
0
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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
51 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
16 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 ...
-1
votes
1answer
44 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
27 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 ...
1
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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 ...
1
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1answer
39 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
vote
1answer
42 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
votes
1answer
178 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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0answers
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
7 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 ...
0
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0answers
81 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 ...
0
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0answers
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 ...
0
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0answers
38 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
59 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 ...
0
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1answer
21 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 ...
0
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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 ...
0
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0answers
20 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 ...
0
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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 ...
0
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1answer
40 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 ...
0
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0answers
34 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
votes
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. ...
1
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1answer
104 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 ...
0
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0answers
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 ...