4
votes
3answers
148 views

Can you compare different clustering methods on a dataset with no ground truth by cross-validation?

Currently, I am trying to analyze a text document dataset that has no ground truth. I was told that you can use k-fold cross validation to compare different clustering methods. However, the examples I ...
0
votes
1answer
68 views

Principles of Time Series Clustering

I would like to understand complexity of time series clustering. Clustering is similarity based, so as a basic step we evaluate distance between to points in a multidimensional space. In time series, ...
6
votes
2answers
131 views

Why only the mean value is used in (K-means) clustering method?

In clustering methods such as K-means, the euclidean distance is the metric to use. As a result, we only calculate the mean values within each cluster. And then adjustments are made on the elements ...
2
votes
1answer
134 views

Performance metrics to evaluate unsupervised learning

With respect to the unsupervised learning (like clustering), are there any metrics to evaluate performance?
-1
votes
1answer
43 views

Is it necessary to split data in clustering like in supervised learning?

I'm learning clustering analysis and one book I read says the clustering model should be applied to a disjoint data set to examine the consistency of the model. I think in clustering analysis we ...
3
votes
1answer
111 views

Self organizing maps vs. kernel k-means

For an application, I want to cluster data (potentially high dimensional) and extract probability of belonging to a cluster. I consider at the moment Self organizing maps or kernel k-means to do the ...
1
vote
0answers
25 views

Anomaly/outlier detection using fuzzy clustering

I understand that fuzzy clustering using FCM produces a membership matrix for the set of data points we feed to it. What characteristics will an anomalous cluster produced during this method have? ...
1
vote
1answer
73 views

Using the self-organizing map for sequences of categorical data

I have a number of vectors of categorical data (ex. {'re','ty','cf', ...} ) and I want to perform an unsupervised learning on them. I came across ...
2
votes
0answers
39 views

Univariate clustering for longitudinal cohort

We have screening information on thousands of patients followed for several years. We also have their cancer outcomes, whether or not such cancers were identified by screening or were otherwise ...
2
votes
1answer
106 views

Is it necessary for a distance measure used in clustering to correspond to some valid vector space?

I have defined an distance measure based on some properties of points. But I'm not even sure that it corresponds to a valid distance in some vector space. Is this a necessary condition for clustering ...
2
votes
2answers
134 views

Choosing which data-point to label (active learning)

For an online unsupervised learning algorithm, data-points are learned sequentially. The performance may improve if in addition to the unlabelled data we have some labelled data-points (i.e. ...
0
votes
2answers
55 views

Compute probability of a grouping being correct

I have an exemplar grouping of objects (each with their own feature vector) into categories. I am then given a new grouping of compeltely different objects, and Iw would like to compute the ...
1
vote
2answers
448 views

Image Clustering with K-means - Postprocessing

I did some clustering on an image (each pixel is an observation that has 5 variables associated with it), I get pretty detailed results but they are a little bit noisey... I think. I used K-means. ...
12
votes
4answers
267 views

How to measure shape of cluster?

I know that this question is not well defined, but some clusters tend to be elliptical or lie in lower dimensional space whilst the other have nonlinear shapes (in 2D or 3D examples). Is there any ...
2
votes
1answer
268 views

Which are the most effective clustering ensembles?

In supervised learning, there are some ensemble methods that overcome others significantly (adaboost or random forests to mention some). Few years later, also ensembles in unsupervised learning were ...
4
votes
2answers
167 views

What are features that distinguish clustering, blind signal separation and dimensionality reduction?

In terms of input -> [process] -> output what are features that distinguish clustering, blind signal separation and dimensionality reduction? From this ...
6
votes
3answers
3k views

Supervised clustering or classification?

The second question is that I found in a discussion somewhere on the web talking about "supervised clustering", as far as I know, clustering is unsupervised, so what is exactly the meaning behind ...
1
vote
3answers
177 views

Can unsupervised evaluation measures for clustering replace a supervised evaluation measure?

Is it possible to have the same evaluation performances when comparing some clustering algorithms using many unsupervised evaluation measures instead of a supervised one ?
1
vote
1answer
319 views

Market / Customer Segmentation - Merging two different segmentations

I have a database where each observation is a person. They were questioned on their attitude towards the consumption of X category of product. I have being using K-means to segment this data. I have ...
6
votes
1answer
275 views

Cluster clickstream data

I've recently entered the realm of machine learning and a project I am working on requires me to cluster users based on the order they visited webpages on a website. I have data in the form of: ...
4
votes
4answers
1k views

Initializing K-means clustering

If I have a certain dataset, how smart would it be to initialize cluster centers using means of random samples of that dataset. For example, suppose I want 5 clusters. I take 5 random samples of say, ...
2
votes
1answer
136 views

Market segmentation based on a time of consumption

I'm an almost graduated applied math student. I do some sporadic work in marketing. I have done a few market segmentation projects. I am soon going to do one which is important to me. I usually ...
1
vote
2answers
525 views

Logging similarities between vectors with R

I'm trying to write a program that automatically groups similarities between vectors. The vectors are comprised of point coordinates. For example (assuming X, Y, and Z are numbers): Data Set 1: [1, ...
2
votes
2answers
543 views

Methods for comparing clustering results

I am doing an unsupervised clustering analysis for a genomics project. This means that I do not know when a particular clustering analysis is good or not. I am running different clustering algorithms ...
5
votes
3answers
639 views

Evaluation measure of clustering (without having truth labels)

I'm clustering a set of data but I don't have truth document that allow me to evaluate the result of clustering (I have unlabelled data), so I can not use an external evaluation measure. In this case, ...
3
votes
2answers
117 views

How to apply unsupervised classification to spatial data

I am trying to learn how to apply unsupervised classification to spatial data. In near infra red satelite pictures; the ocean is dark and the forest is white. Each pixel in such an image is an ...
1
vote
0answers
65 views

SOM automated/objective clustering

So as I understand it SOM is primarily a visualization tool and clustering is a logical next step after you construct a SOM from data. Typically, the clustering is subjective in that after looking at ...
8
votes
2answers
196 views

SOM clustering for nominal/circular variables

Just wondering if anyone is familiar with clustering nominal inputs. I've been looking at SOM as a solution but apparently it only works with numerical features. Are there any extensions for ...
3
votes
1answer
402 views

How can I assess how descriptive feature vectors are?

I am assessing how good different features are for unsupervised classification of a set of objects. For each different feature I test, I have computed a feature vector that describes the object. I ...
14
votes
1answer
5k views

How to define number of clusters in K-means clustering?

Is there any way to determine the optimal cluster number or should I just try different values and check the error rates to decide on the best value?
4
votes
0answers
236 views

Recommended method for finding archetypes or clusters

I wish to cluster users together in a database, with each user represented by a number of features that are both discrete and continuous in nature. The aim is to define a small number of archetypal ...