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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5 views

what is Gower distance? How its a good measure for clustering?

I am bit confused about Gower distance. It can handle all types of data. can someone detail me how?
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6 views

Using KNN or Clustering techniques to increase data sample size

had a question regarding using KNN or clustering techniques to 'pad' smaller data sets with similar data points. Say, I have some data, a modified and simplified snippet of which looks like this: ...
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0answers
13 views

Random forest clustering

In my data the classes were defined by binning a variable in 10 bins. After growing the random forest its proximity matrix is viewed as the following MDSplot: As can be seen from the plot all ...
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0answers
9 views

Multidimensional time series clustering

I have unemployment rates and interest rates per country over time. I want to cluster the countries that have similar dynamics and levels in both dimensions together. What could be a reasonable ...
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0answers
8 views

Characterizing clusters by separate feature vector scores

Say I have a medium amount of dependent variables in a study. These are scores from questionnaires that have been standardized so all are on a scale from 0 to 1. I have clusters of my patients - ...
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0answers
10 views

Using Pelora function in R [on hold]

Although I examined the usage of pelora function which is under supclust library, I can't get why it uses. Is there anyone that explains how it works and what pelora function is ?
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1answer
19 views

Create clusters subject to constraint

I have a set of nodes. Each node represents a building and it has some attributes. For example: x coordinate y coordinate population What I want is to create ...
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2answers
85 views

X-means algorithm and BIC

I want to simulate X-means algorithm based on [1] in MATLAB. I have some questions about this algorithm. X-means Algorithm Steps: (1) Initialize K = Kmin. (2) Run K-means algorithm. (3) FOR k = ...
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0answers
25 views

MapReduce implementation of Fuzzy K-means [on hold]

please help me out here. I needed your help in guiding me about implementing fuzzy k-means clustering algorithm in mapreduce using R langage.
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0answers
19 views

Is it possible to use WEKA in a web based application? [on hold]

I am building a web based text mining application. For a word that user enters, the application has to: search it in google gather the documents pre-process by using Bag of words model cluster ...
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12 views

Clustering without multiple variables

I want to cluster a set of schools according to their academic performance (using the marks of students from each school for a special exam). But the data set only contains the name of each school and ...
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0answers
13 views

DCCA clustering algorithm understanding

I try to understand the step 2.5 of the DCCA clustering algorithm pasted below. The original reference is here and the PowerPoint presentation is here. I have the following questions: Do we perform ...
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0answers
11 views

Correlation analysis and Clustering in R - Some suggestions [on hold]

I have a biological data, comprising of intensity values associated to 24 masses. Each mass file has 10,000 intensity values corresponding to 10,000 coordinates. So, the data matrix in R would look ...
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1answer
15 views

Clustering a list of restaurant dishes

If I have a large list of restaurant dishes that all have the same cuisine... (Pulled Pork, BBQ chicken, 1/2 Ribs, Pork Sliders, Slow Smoked Pork, Full Chicken Special....) What would be a good ...
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1answer
28 views

Hierarchical cluster analysis with a similarity matrix [on hold]

I am trying to analyse the results from a card sorting study i did, but all i have is raw data. I have the similarity matrix for 53 cards, but I am trying to figure out how to do a hierarchical ...
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1answer
33 views

k means clustering on sales geolocation data

I have geolocation data (lat and long) per customer per online purchase, and my end goal is to identify common locations per purchase per customer. (basically to see what people typically buy when ...
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0answers
16 views

Appropriate cluster method for 7-point scale data of 58 variables and 635 observations

My research buddy and I are conducting cluster analysis on survey data using a 7-point relevance scale (1=Not relevant, 7=Extremely Relevant). We have 58 variables, arranged in 10 groups of ...
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2answers
37 views

How much variation should a clustering algorithm explain?

When running a cluster analysis, the algorithm used normally returns a measure of how much variation the clustering explains. e.g. "This clustering explains 96 % of the variation in the data" ...
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0answers
21 views

Choosing k in consensus cluster plus using cophenetic correlation coefficient

I am trying choose best k from the consensus clustering using the Cophenetic Correlation Coefficient (CCC). I tried as follows. The correlation coefficients values are poor, i.e., ...
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0answers
13 views

Clustering headlines without full text [closed]

I have a data-set with headlines of news. The number of topics is 100. Also I have a tf-idf file, which is not generated by me. I saw data-set, and I can determine something like 50 clusters. 50 - ...
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0answers
10 views

Clustering on SVM results?

I have a data set with many subjects. Within each subject, I've run linear SVM to classify two types of stimuli that they see. The decision boundary is different for each participant, as would be ...
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0answers
5 views

Clustering in R - Clara [migrated]

I just started using R and was trying to cluster with Clara. I am not getting quite the results I had hoped for, and was wondering where I could find the details of the implementation of the algorithm ...
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0answers
18 views

Clustering an image using Gaussian mixture models [closed]

I want to use GMM(Gaussian mixture models for clustering a binary image and also want to plot the cluster centroids on the binary image itself. I am using this as my reference: ...
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0answers
16 views

Diagnostic regression for checking the validity of clustering results

I have done an unsupervised non-parametric clustering on sample data gathered by a questionnaire for my thesis (k-means algorithm). A referee asked me to do a diagnostic regression for checking the ...
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18 views

Clustering algorithm advice for extracting key features in sparse data

I have the following dataset: consider a dataset $X$ of $1400 \times 600$. The rows represent households at time $1 \leq t \leq 14$. So I have $100$ households. The columns represent the programs that ...
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1answer
17 views

Cluster Analysis on GPS data - Assigning GPS coordinates to core groups

I'm trying to figure out a way to assign GPS coordinates to core GPS values. For example, I've got tons of store locations (with long & lat coordinates) and I'd like to group them to one of x ...
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0answers
99 views

R: silhouette with k-means

I'm currently checking some clustering evaluation indexes in R, and now I'm using Silhouette and its respective function in R, "silhouette" (in "cluster" package). To test the method, I used the ...
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1answer
97 views

What type of analysis to choose for this data?

I am trying to create a model of refrigeration having the energy consumption and the temperature over time. So far, I've tried regression but fitting this data into linear model seems impossible. ...
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12 views

Finding influential characteristics in a chain of events

I have some data which is sequences of actions performed by individuals. All of these actions have properties (some catagorical, some binary, some continuous numeric). Individuals can have 1 to ...
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9 views

Why do we need to normalize data into interval [0,1] in subtractive clustering? How about Z-score?

I read that we need to normalize data into interval [0,1] in subtractive clustering. Is there any difference if we standardize data into Z-score or other interval instead of normalize it into [0,1]?
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22 views

Statistic to measure grouping (or intensity) of observations

I'm looking for a statistical technique that can measure the level of grouping or intensity of observations. I'm not sure what the proper terminology is, so I will try to explain my question through ...
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4answers
63 views

How do you cluster data such that each cluster satisfies a condition (such as “diameter of each cluster can't be larger than 10”)?

I would like to run some kind of clustering algorithm on my data (which can be thought of as a collection of vectors). I do not want to start with using k-means because I do not know what ...
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1answer
20 views

Outlier detection using clustering on few rows

I have a frequency table (2 columns) of 20 rows of various transaction amounts. Some of these amounts are fraudulent in nature and are pretty obvious as they appear to be outliers in the scatter ...
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0answers
7 views

Understanding divisive clustering code

I came across divisive clustering algorithm (Cichosz, P. (2015) Data mining algorithms: Explained using R; page 262), which is implemented in R. The appropriate function is pasted below. Actually, I ...
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0answers
11 views

Gower Distance, Ordinal Variable, R, Error?

I am trying to implement the CritCF function from http://www.sciencedirect.com/science/article/pii/S0031320310004905 for feature selection in clustering. I need to compute the distance from cluster ...
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9 views

Classify users by the pages they liked

I have a data set of users, and a list of pages each users liked. My goal is to derive k classes of users. I was thinking of applying ...
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2answers
45 views

How to define clustering in R

The data contains information about the genes causing breast cancer in our body. My aim is to find the most effective gene on breast cancer in our body. The code that I have first divides my sample by ...
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0answers
28 views

are there anomalies? and if so, can I quantify them?

Given a data set, I want to divide it in two different sets if I see that part of the data misbehaves. For example, in the figure you can clearly see that something is happening before the vertical ...
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0answers
32 views

Defining clustering in R [duplicate]

The code that I have first divides my sample by clustering and then shows number of genes which can separate samples into those clusters. To do the second function it uses " mRMR.classic ...
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3answers
135 views

How do I determine whether my data is spherically separable?

Is there a simple statistical test that I can use to determine whether my data is spherically separable? I am planning to use Kmeans++ to divide 48 dimensional vectors into clusters but I just read ...
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0answers
20 views

K means algorithm on an image

Hi I want apply my k means algorithm on an image to a certain number of k clusters.I want to ask is that How is the algorithm applied ? I mean what i have learned from internet is that k means is ...
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1answer
16 views

Clustering when similarity/affinity matrix is binary

I have n articles and a list of articles for each article implying similarity, e.g., a1 -> a3, a5 means ...
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1answer
26 views

Identifying the border between two clusters?

I have three variables which I have graphed as a scatter plot. One for x, one for y, and one for whether the point is red or blue. There are clearly two clusters - one red cluster, and one blue ...
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0answers
37 views

What could cause a K-means clustering algorithm to converge into a single cluster?

I am currently writing a K-means clustering algorithm in Python, and I seem to have coded myself into a corner... I begin my algorithm with data sets assigned randomly to the appropriate number of K ...
2
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1answer
43 views

Community detection (graph clustering) of a weighted graph with node attribute (categorical or quantitative)

Consider a weighted graph having node attributes. Say the nodes are birds and the attribute could be either categorical (gender) or quantitative (number of feathers), i.e. similarly to this example. ...
3
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0answers
60 views

How to build “supervised clustering” for neural networks?

I'm confused as to what the output would be. Consider the "blind source separation" problem. Let's say I have a ton of training examples where the input is the final cacophony of sounds as a sound ...
2
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1answer
26 views

Sequence analysis - Clusters quality - Time Use

I am trying to run sequence clustering on time use data but I fail to have "acceptable" clustering solution according to Studer (2010). The sequences have 76 episodes of 15 minutes slots (12 ...
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0answers
13 views

Weighted zone scoring in clustering

I have a bunch of documents, and I'm trying to understand them, using machine learning. A first step would be clustering, which I've already done and works fine: ...
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0answers
38 views

Clustering transactional data with R [closed]

I have a dataset with 3.205 observations and 6 variables about viewing habits from Rio and Sao Paulo in Brazil. They're supposed to have different habits so I need these data to form natural clusters ...
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2answers
36 views

How to measure cluster quality with distance matrix?

When performing clustering with an algorithm such as K-means, it's possible to construct a plot that shows the intra cluster variability according to the number of clusters to see if there is an elbow ...