3
votes
0answers
30 views
Which variables are driving correlations within groups
I'm running an analysis on a few data sets that each typically have 100-200 cases measured across 120-160 variables - something similar to looking at gene expressions. Each variable is a non-centered ...
2
votes
1answer
115 views
+100
Select best set of binary variables for clustering known sample labels
I have a set of samples, for which I know the "true groups". For this samples I have about 200 binary variables, I would like to know a method to select the subset of variables, that gives me a ...
0
votes
1answer
44 views
Fit of a normal distribution to a one-dimensional dataset in R
I've got a set of (continuous) values from a measurement, where each object should be either positive or negative, and I know that the values of the "negative" objects should be approximately normally ...
2
votes
0answers
36 views
Clustering longitudinal (trajectory) data
I am hoping to implement an unsupervised technique that identifies distinct clusters of individuals based on longitudinal data: 100 continuous or categorical variables measured at different ages.
A ...
0
votes
2answers
47 views
Time Series Similarity : Differing Lengths with R
I am experimenting with creating a distance matrix between time series for clustering and similarity searching. The main reference I am using is for the Similarity procedure in SAS (Paper). I would ...
1
vote
2answers
51 views
Persistent cluster IDs over similar inputs with k-means
I have multiple kmeans plots that I have generated in R. Specifically I have $5$ weeks and I generate $1$ kmeans plot per week. ...
1
vote
1answer
40 views
How to explain how I divided a bimodal distribution based on kernel density estimation
I have a dataset of bimodal population. It contains a smaller peak, which is considered to be "bad", and a bigger peak. I try to separate the bad part of data from the rest of data. What I did was: ...
1
vote
2answers
101 views
Cluster analysis on ordinal data (Likert scale)
I want to do clustering of my data in R, using kmeans or hclust (I am a new R user).
My data is ordinal, Likert scale, to measure the causes of cost escalation. I have 41 causes "variables" that ...
1
vote
1answer
47 views
Dummycoding based on clustering from OM distances
I'm using TraMineR to determine a certain clustering based on Optimal Matching distances:
...
4
votes
1answer
90 views
Finding a known number of circle centers that maximize the number of points within a fixed distance
I have a set of 2-D data where I want to find the centers of a specified number of centers of circles ($N$) that maximize the total number of points within a specified distance ($R$).
e.g. I have ...
3
votes
2answers
154 views
Cluster Big Data in R and Is Sampling Relevant?
I'm new to data science and have a problem finding clusters in a data set with 200,000 rows and 50 columns in R.
Since the data have both numeric and nominal variables, methods like K-means which ...
2
votes
1answer
123 views
K-means & BIC (to validate clusters) in R
I'm wondering if there is a good way to calculate the clustering criterion based on BIC formula, for a k-means output in R? I'm a bit confused as to how to calculate that BIC so that I can compare it ...
0
votes
0answers
44 views
How should I cluster my data and then run separate algotithms on each cluster?
I'm new to statistics and R. So, I have a dataset on which I want to build a predictive model.
Since there is quite a variability in the input variables, I thought it would be better to cluster my ...
4
votes
1answer
163 views
What is an acceptable value of the Calinski & Harabasz (CH) criterion?
I have done a data analysis trying to cluster longitudinal data using R and the kml package. My data contains of around 400 individual trajectories (as it is called in the paper). You can see my ...
1
vote
2answers
75 views
Sparse hyperspace clustering
I have a dataset of M elements where every item is represented by a feature vector of length N where N is very large and only a small subset of N is bigger then zero for every item. So I have a sparse ...
2
votes
1answer
196 views
Choosing clusters for k-means: the 1 cluster case
Does anyone know a good method to determine if clustering using kmeans is even appropriate? That is, what if your sample is actually homogenous? I know something like a mixture model (via mclust in R) ...
1
vote
1answer
144 views
Comparison of k-means clustering output
I am trying to compare the outputs of k-means algorithm coded by me and the outputs of R's kmeans. Since the objective of the algorithm is to minimize the total ...
0
votes
0answers
132 views
R statistics: Adjusted Chi-squared test for clustered binary / categorical data
I'm looking for some assistance in statistical analysis with R, but also some general stats advice.
I am analysing cardiac phenotype data by comparing 2 groups. The 2 groups are unmatched ...
0
votes
0answers
83 views
R is taking ages to cluster documents, what other options do I have?
I was trying k-medoids algorithm for clustering in R, and just removing stopwords is taking hours. After I removed stopwords, I let the algorithm run overnight and it wasn't done after 8-9 hours. I am ...
0
votes
0answers
45 views
How can I run a hierarchical clustering on a data set with categorical variables in R? [closed]
how to run a heirarchical clustering on a data set with categorical variables in R?
Also how to run a hierarchical clustering task with selected attributes (lets say varibales V1,V3,V4) and display ...
1
vote
0answers
158 views
How to choose clusters from variable clustering (varclus) procedure?
I am attempting some variable reduction before I perform a logistic regression. I am quite interested in using Hmisc::varclus in R. However, I am having some ...
1
vote
2answers
229 views
R: Visualizing document clustering results
I have a k-means clustering result with 35 clusters, there are 5000 documents that each belong to one of the 35 cluster. I would like to visualize the results of the clustering algorithm on a scatter ...
1
vote
2answers
408 views
Interpreting result of k-means clustering in R
I was using the kmeans instruction of R for performing the k-means algorithm on Anderson's iris dataset. I have a question about some parameters that I got. The ...
4
votes
1answer
107 views
Index plot for each cluster sorted by the silhouette
After a cluster analysis I´m trying to plot for each cluster the Index plot of the Silhouette value instead of for the complete dataset
(like in the WeightedCluster Library Manual by Matthias ...
0
votes
1answer
111 views
Density Clustering
I am looking for a clustering algorithm. My idealized dataset looks like this:
The clustering result should look like the Rapidminer density plot:
Means 3 or 4 clusters should be the clustering ...
2
votes
1answer
200 views
Does SPSS rescale dendrograms?
A colleague and I have been clustering some data in SPSS (v19) and R (2.15), respectively. Using the same distance metric and agglomeration method, we get identical merge orders/agglomeration ...
2
votes
2answers
282 views
Clustering high-dimensional sparse binary data
I am trying to cluster Facebook users based on their likes.
I have two problems: First, since there is no dislike in Facebook all I have is having likes (1) for some items but for the rest of the ...
2
votes
3answers
287 views
Which type of regression fits better?
I am a newbie in data mining world. I have a general question.
I have a data set which has 10 independent variables and one target variable named as category which has 9 values like: 1, 2, 3, 4, 5, 6, ...
0
votes
1answer
33 views
Clustering with the same number of objects per group
How can I cluster while forcing the final clusters to have more or less the same number of objects?
I have just tried kmeans in R, and it does not take this into ...
5
votes
2answers
189 views
Calculating similarity and clustering question
I have a dataset of about a million companies containing their names, total employees and annual sales. I want to come up with a function that when given the company returns the 5 most similar ...
2
votes
1answer
51 views
Which metric use for problem of clustering spatial data of wind direction and speed?
I have two dimensional spatial (x,y - coordinates of meteo stations) data for small region (so I could neglect the shape of earth globe), for each (x,y) I have one observation of wind direction and ...
1
vote
3answers
100 views
How can I separate each of 100 observations into groups as determined by the data?
I have 3 covariates for 100 observations. How can I separate each of my 100 observations into groups as determined by the data. I was thinking clustering. However, apparently, I need more than 3 ...
3
votes
3answers
356 views
How to reduce the number of variables in cluster analysis?
I've got 10 (yes, only 10) cases over 1000 variables (e.g. measurements of concentrations of 1000 different compounds at 10 different time points).
I can group these cases into 3 clusters in ...
0
votes
1answer
150 views
Clustering time series with wavelets in R
Can discrete wavelet trasform be used for feature extraction from time series in order to cluster them? Any R code how to do this will be appreciated.
2
votes
0answers
130 views
Clusters produced by R intersect
I am new here - and relatively new to statistics, data mining and R. I am trying to understand why my data is not clustering correctly - or if I am reading it wrong. Shortly about the project:
My ...
3
votes
1answer
84 views
Finding “weak ties” in network data
So I am working on a new project looking at formal and informal networks between businesses in the same industry. Namely, I am looking at joint ventures, fractional acquisitions, minority share ...
1
vote
2answers
168 views
Specifying the number of clusters in nearest neighbor clustering
I've got a distance matrix between examples. I want to cluster them into m clusters with a nearest neighbor algorithm which works like this:
...
2
votes
1answer
462 views
1
vote
1answer
169 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 ...
4
votes
1answer
343 views
Fuzzy K-means - Cluster Sizes
I'm trying to do fuzzy k-means clustering on a dataset using the cmeans function (R) . The problem Im facing is that the sizes of clusters are not as I would like them to be. This is done by ...
4
votes
1answer
628 views
Is there an R function that will compute the cosine dissimilarity matrix?
I would like to make a heatmap with row clustering based on cosine distances. I'm using R and heatmap.2() for making the figure. I can see that there's a ...
2
votes
1answer
119 views
Nonnegative matrix factorization on a matrix with negative values
I have a gene expression profile with negative values.
Is there any way to do an Nonnegative matrix factorization (NMF) on a matrix which has a few negative values?
(I couldn't approximate the ...
1
vote
0answers
293 views
Cubic clustering criterion in R
Does anybody know if any package calculates the cubic clustering criterion (CCC) index in R to aid the selection of optimal number of clusters?
2
votes
1answer
822 views
Dirichlet process/Chinese restaurant process for clustering in R
I recently read a fascinating article describing methods for clustering data without assuming a fixed number of clusters.
The article even includes some sample code, in a mix of Ruby, Python, and R. ...
0
votes
0answers
63 views
How do I do group wise clustering in R?
How do I do group wise clustering in R?
Hi all,
I have N x K data matrix, where N is the number of observations, K is the number of variables.
The N observations fall into M categories or groups.
...
1
vote
2answers
396 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, ...
1
vote
1answer
137 views
Cluster analysis of boolean vectors in R
I have 114 vectors with 6 boolean attributes. I saw that might be several distinct clusters in a simple visualization. K-means clustering on the transformed vectors (true = 1, false = 0) results in ...
3
votes
1answer
178 views
Cluster analysis in R produces reversals
I'm attempting to perform hierarchical agglomerative cluster analysis in R.
However, when I use particular clustering methods, I get reversals (upward branching) in the resulting tree, which ...
1
vote
2answers
574 views
How to determine the number of clusters when using correlation as the distance?
How does using 1 - correlation as the distance influence the determination of the number of clusters when doing kmeans?
Is it still valid to use the classical indices (Dunn, Davies-Bouldin...)?
0
votes
2answers
565 views
How to input self-defined distance function in R?
I want to know how to to input a self-defined distance in R, in hierarchical clustering analysis. R implements only some default distance metrics, for example "Euclidean", "Manhattan" etc. Suppose I ...
