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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30 views

Datasets for market segmentation

What are the gold standard datasets to test market segmentation algorithms with? I'd like to try a few algorithms on known datasets for comparison before I try my own dataset.
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1answer
39 views

Is there such thing as correlation trees? Clustering rows of X based on correlation between A and B

I have been searching for several days for a method that fits this description, though cannot find one. I'm pretty sure it must exist. The problem (short version): I'd like to run something like a ...
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0answers
41 views

Groups in linear regression with different intercepts. How do I find the differing variable?

This is more of a conceptual question. I have a coefficient estimate of .80 in a linear regression model with one IV and one dependent variable. However, plotting the data I see distinct groups, ...
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2answers
58 views

Finding independent “clusters” in a matrix

I've called my question "clustering" but I am not sure if that's the right term. Imagine my matrix looks like this: ...
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1answer
22 views

Searching for time series inside another time series

I have a time series "A" and another one "B". I would like to find occurrences of "B" inside "A". Typically, "A" is much bigger (magnitude: millions of points) than "B" (magnitude: hundreds of points) ...
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0answers
30 views

Using the coefficients of regression for giving weight to the data

I want to perform clustering on my data set. I used spectral clustering and obtained an acceptable result. In an effort to (maybe) improve the result, I thought of applying a linear regression on my ...
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1answer
49 views

Clustering of items based on their category belonging

I am trying to find a clustering algorithm, but I'm working with already classified items. Basically, items belongs to one or more category, which are already known. Categories are absolutely not ...
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1answer
96 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
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1answer
38 views

A clustering and classification question

I'm trying to classify my set of data into two classes (introvert / extrovert). I was thinking of using a decision tree at first, but I don't have any potential known results in order to create my ...
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1answer
43 views

Clustering a completely interconnected graph with weighted edges

I was wondering if Markov Clustering is what I really am looking for or not. Basically I have a N node graph in which every node is directly connected with one another. However, all the edges are ...
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1answer
41 views

cluster analysis, Ward: how to evaluate number of clusters and their quality?

I have a table of similarities (cosines) and I clustered it with the Ward method. Great outcomes, a wonderful dendogram, but then I tried to evaluate the quality of this cluster solution and I got ...
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1answer
142 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 ...
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1answer
33 views

Classifying a set of photos to places

I want to cluster photos and map them to places. As input I have Photos with locations (lat, long) Places - some as (imprecise) bounding boxes, some just as points, maybe others as bounding ...
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2answers
61 views

clustering accuracy

I have a general doubt regarding clustering. I have a data set of size 1196*18675. where 1196 is the no of documents. I am trying to cluster the data with k=7 using k-means. Each time the clustered ...
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0answers
21 views

Setting up feature vectors

I am working on a classification project and I want to use SVM's and/or Clustering Algs. What I am having trouble with is deciding how to set up my feature vectors. I have already decided what my ...
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1answer
66 views

using cluster information in multiple imputation

i need to impute a dataset all categorical variables before doing analysis. I can just simply impute with mode of all data or a variable. I belief that better option will be to classify the subjects ...
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1answer
27 views

What method to use for cluster identification ?

This question is from a confused novice. I have a data set with where each point is located in a 2-D space defined by two objectives (say, X and Y). I wish to identify a set of points from this space ...
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0answers
75 views

(Spatial) distance between cluster means

I'd like to cluster points based on a distance criteria. As I want to cluster spatial points I am using euclidean distance and a hierachical cluster approach. In a final step I'd like to cut the ...
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0answers
19 views

Cluster analysis of open-question responses

I am currently analysing a 1100-observation dataset of open-question responses. I was wondering whether I could really do a segmentation based on these responses. What I've done is so far is ...
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1answer
42 views

Is it posible to perform the inverse of multidimensional scaling analysis

We have lot of 3D data and we reduced it to 2D for performing fuzzy clustering and obtaining prototypes. We used some matlab functions that were very well documented. Now we would like to see to which ...
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2answers
123 views

Excel: which products are most frequently ordered together? (clustering question)

I'd like to recruit your help in coming up with an Excel-based method to analyse a set of raw ordering data where each item is on its own row. So, in the data below, order 111 contains two part ...
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0answers
39 views

Reducing high dimensionality as well as feature selection on multivariate time series

Lately I've been reading a lot about time series clustering as I want to search for similar patterns in my own data set. Even though I feel like I understand the basic concepts of this task I still ...
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0answers
19 views

Turning MiniBatchKMeans into Fuzzy MiniBatchKMeans

I'm using Scikit-Learn, which has an implementation of MiniBatchKMeans. I'm very inexperienced with ML, so I'm wondering how (if ...
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4answers
304 views

Clustering binary categorical data

I have some data where I have certain classes (c1, c2, c3, c4 ...) and the data comprises of binary vectors where 1 and 0 denote that an entry belongs to a class or not. The number of classes will be ...
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0answers
57 views

Spectral clustering using RBF Kernel function in R

I have extracted user-features and item features in my recommender system using a modified SVD approach built on ALSE (loosely based on Yehuda Koren's paper). I now want to cluster items not directly ...
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1answer
43 views

Which clustering technique to use for a temporal dataset?

I have seen a similar question but thought I'd ask my own to hopefully garner some usefull feedback. Basically, I have a large temporal dataset, consisting of domestic smart energy meter use ...
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1answer
32 views

Cluster Analysis Sample Size for Diss Proposal

My psychology dissertation will be a cluster analysis with one grouping variable. How do I know how many participants I need? I imagine there should not be more than 5 clusters. 79 items make up 9 ...
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0answers
22 views

Suitable plot for 5 dimensional feature vectors?

I have a list of personality scores obtained from 100 people, based on the Big-Five personality test. Each person has one score for each of the five assessed traits. I put these scores into a 5 ...
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1answer
19 views

Need help understanding response from Metis

I was wondering if any of you could help me understand the response I got from this clustering algorithm (Metis). As you probably can see, I'm trying to cluster IP addresses based on common records ...
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0answers
27 views

Anomaly detection for one feature vector

I have a $n$-dimensional vector of ordered multiple testing $p$-values and I would like to reject the first values that are under a certain threshold $\alpha$. I am looking at this problem as an ...
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0answers
53 views

Determine Number of Clusters Using Silhouette Method and Distance Matrix

I have a tree and its associated distance matrix. Now I want to cut the tree to give a desired number of clusters. Luckily there are a number of methods for determining the number of clusters as ...
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0answers
79 views

Unsupervised Random Forest for Visual Codebook generation

I'm trying to apply the bag of visual words approach to make scene classification. I started to use k-means to generate my codebook, but rapidly discovered its limitations. From one codebook ...
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1answer
25 views

On the connection between SSE and absolute deviation from the centroids

Is there any connection between sum of squared error SSE and the absolute deviation from the centroids after clustering. More formally, I have clustered $T=\{x_i\}, i\in\{1,\ldots,n\}$ and the ...
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0answers
60 views

Performance of hierarchical clustering for binary data in R

I am trying to use Hierarchical clustering to see how well it performs in classifying a dataset which I previously know its true classification. I am new to clustering in general. I was able to draw ...
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1answer
68 views

Best metric for evaluation of mixture-of-Gaussian clusters on big-data

I have made a new algorithm that is specifically crafted for clustering very large datasets. In order to document it as a research paper, I have to choose one or two internal (no-label) cluster ...
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0answers
5 views

How to identify a subset of effects as the drivers of significant differences?

Okay I will explain this as best as I can. I have an additive risk score for each of my observations (i.e. I'm putting 100 individual effects into a single variable). The means of this risk score ...
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1answer
33 views

How to reduce number of points for clustering

Description I have to find number of clusters for 1D data. All clusters are assumed to have a gaussian distribution (so there is a big number of same points). I have a robust "aglomerative clustering ...
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1answer
35 views

Assigning meaningful cluster name automatically

The objective of my work is to cluster the text documents. Once the documents are clustered, traditionally the system will assign numeric value for the clustered group. For example if I have 5 ...
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1answer
70 views

Identifying subsets for outlier detection in local outlier factor

I am trying to gain better understanding of the idea of local outliers (as discussed in this pdf) and how the function is implemented. Here are the key passages from the pdf: Local outliers: ...
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1answer
44 views

Cluster analysis on time series samples

In the follow-up to this Ways to understand 2-dimensional time-series data I'm working on 2D time series data where two attributes are depth and temperature. When I plotted depth-vs-temp curve and ...
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0answers
118 views

Cophenetic distance matrix to a dendrogram

In hierarchical clustering procedure, a distance matrix is used to construct a dendrogram with an appropriate method of clustering. In the process of constructing a dendrogram, a cophenetic matrix is ...
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1answer
53 views

Extract (ultrametric) distances from hclust or dendrogram

How can the matrix of (ultrametric) distances be extracted from the result of hclust (or a dendrogram in general) in R? The ...
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1answer
81 views

K-means cluster Analysis and 4-point Likert Scales

Is there a concern using a 4-point likert-type scale (i.e., agreement) when attempting a cluster analysis using k-means clustering? Most of the data for the items in my data set are favorable (e.g., ...
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0answers
31 views

Clustering coefficient for a clique

I would like to understand how to solve this exercise about clustering coefficient for a clique. As shown in the picture below if node pairs (a; b), (a; c), (a; d), (b; c), (b; d) are linked, then the ...
2
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1answer
51 views

Selecting number of clustering classes automatically

I am working in text clustering. I would like to find a way to identify the number of classes for the clustering process automatically rather than proving the number of class manually. Is their any ...
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0answers
18 views

Heuristics for unsupervised or semi-supervised approaches to GIS coordinate data

I have a more conceptual/heuristic question about how to go about formulating a problem in order to take a semi- or unsupervised method of solving it. I'm working on a project with data collected ...
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1answer
43 views

Implementation for Co-Clustering

I am looking for existing implementations for co-clustering (aka biclustering). I came up with biclust function available in MATLAB, but still I am wondering if ...
0
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1answer
56 views

Combine Clustering and classification

I have a receipt database of a grocery store. I would like to find classes of similar customers based on their receipts and classify people after their shopping to one of these classes. Let us assume ...
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0answers
21 views

Deriving distance function based on multiple variables

This question is in relation to the following answer of yours: How to derive a distance function based on multiple variables for cluster analysis? Suppose I have 7 variables, each quantitative (and ...
3
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2answers
114 views

Feature / attribute selection for k-means or other clustering

It seems to me that in literature it is assumed that one knows which features / attributes to choose to characterize an item in clustering. If I have a database with items which have many attributes, ...