0
votes
3answers
33 views
Clustering mixed variables in SAS
I have following variables in my dataset:
Working hours (numerical:ordinal)
Effectiveness (categorical:ordinal ; 4 values-> (poor,average,good,best))
Satisfaction (categorical:ordinal ; 4 values-> ...
2
votes
1answer
106 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 ...
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:
...
3
votes
0answers
55 views
Cluster on high dimensional categorical data (Images with keywords)
We're looking for clues to perform a Cluster Analysis in a DB with +400K images which have keywords associated to them.
Each image could have from 1 to 30 keywords.
Total keywords count is +35K.
...
1
vote
1answer
99 views
Cluster analysis on weighted survey data with continuous and categorical variables
I am trying to perform cluster analysis on survey data where each respondent has answered several questions, some of which have categorical answers ("blue" "pink" "green" etc) and some of which have ...
1
vote
0answers
29 views
For count data from a survey, do variance corrections for survey design imply that the Poisson distribution will not accurately model the counts?
I have categorical count data that comes from a complex survey. Each unit of analysis in the survey (household, individual, etc.) is put into one and only category per dimension, ranging from 2 to 20 ...
1
vote
1answer
36 views
Generating rules to obtain a given categorical distribution… is it possible?
I'm working on a problem, I was wondering if there are any methods available to do the following.
I have a data set with information on people (continuous and categorical data). I have 3 categories ...
2
votes
2answers
362 views
Why don't dummy variables have the continuous adjacent category problem in cluster analysis?
I know that if we use categorical variables in cluster analysis we would assume that the scale is continuous and we don't have this concept of distance between two adjacent categories.
But what is the ...
3
votes
1answer
360 views
Ecological mixed data cluster analysis: Transformations required? Use K-means or hierarchical methods?
I am trying to identify habitat types from 85 plots. I intend to do a cluster analysis to identify habitat types, and hope to fit additional plots into the identified clusters.
(For context, I took ...
3
votes
1answer
411 views
How to convert molecular categorical variables to dummy variables for cluster analysis?
I would like to use a clustering method, e.g. 'mclust', in R to classify each individual in my dataset to k groups. I have 7 continuous and 3 categorical variables. These and other hierarchical ...
3
votes
0answers
69 views
R: looking for “time” clusters in a data set
I am new to R and seeking some advice. I have a set (~20M) of data describing on which step a process did fail or succeeded:
...
3
votes
2answers
202 views
How should I classify stores based on the demographics of their customers?
I've got a dataset of demographic details of store customers and which store they (most frequently) visit. I would like to categorize the stores based on their customers.
To clarify: The issue ...
3
votes
0answers
214 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 ...
