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Questions tagged [hierarchical-clustering]

Hierarchical cluster analysis is a method of cluster analysis which builds, by steps, a hierarchy of clusters, a dendrogram. Most popular is agglomerative hierarchical clustering (HAC) which starts from individual objects and collects them into bigger and bigger clusters.

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Clustering with constraint on minimum size of cluster

I have dataset of $n$ objects, I want to cluster them according to correlation and I want to divide the dataset into groups of similar objects of sizes not less than 50 - because I use clustering for ...
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What does each cluster represent?

I have a dataset from a questionnaire with over 10000 rows and 30 variables. I am trying to have an insight of the data so I tried to cluster similar items. I first made a dimension reduction ...
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Ward's minimum variance clustering in R_Another title for y-lab = Height? [on hold]

I've done hierarchical clustering using hclust (distance, method = ward.D2) in R and got the following graph. Can I use another word for y-axis label instead of Height? Is it acceptable to say ...
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Hierarchical clustering: Should I first normalize / correct for phenotypic data?

I've a set of N=100 samples, each sample having M=10 variables (100x10 matrix). These 10 variables (M_i) are responses to some drugs. In addition I've for each sample a list of phenotype data (...
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jaccard distance if one samples is a subset

I have a very basic question but I cannot find an answer (especially for a clustering situation). I am trying to do hierarchical clustering of samples using jaccard distances. One sample contains ...
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Total variance calculation in hierarchical clustering

I've clustered my data variables using ClustOfvar in R and got three clusters. How would I calculate total (global) variance explained by these three clusters for the dataset? ?
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Multi variable clustering cartographical data

Firstly , my knowledge in statistics is very limited , so excuse me if I'm ask a none well placed question. I have a country ,( example : USA ) , and i have 3 set of data 1) position (lat , lng ) ...
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Can I view the features of my clusters without doing it by hand?

I have performed hierarchical clustering on a data set with 186 participants and 94 variables for each participant. What I want to know is if there is a way to see which features are "driving" my ...
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How to cluster a (directional) dissimilarity matrix with both positive and negative values?

I may be thinking of this incorrectly but what would be the best way to cluster a dissimilarity measure that has direction? For example, if someone had condition A ...
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Characterisation of Hierarchical clusters

I have clustered my observations, n = 615, following the cluster of variables in my data, to see if the observations make some sense too. I've got this dendrogram and want to know which observations ...
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34 views

R: What is the distance function equivalent for this formula?

Hi I'm using an R package that calculates distance with this formula here, as.dist(1 - cor(df, use = "pa")) However I cannot seem to find an equivalent dist ...
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Why clustering metrics are worse while adding some features?

I am facing something unexpected at first sight and would like to know if you could share some insights. Basically, I have performed a clustering on both qualitative and quantitative data using the ...
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Decision Tree from Agglomerative Clustering

I have agglomerative clustering done. I want to convert it to a decision tree so I can figure out the cluster very quickly. How to do so? A tedious approach (bad, I know): Take the top ...
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Clustering for medium data [closed]

Which clustering method is good in R for a data with ~32,000 subjectsa and 10 variables, hierarchical or k-means?
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How to tell if the “clusters” I see in my pair plots are statistically significant or occurring by chance?

I have a data set with one row per subject. Some variables include laboratory parameters for blood chemistry, hematology, etc. I also have some flag variables: any = 1 if the subject experienced an ...
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How to use a previously calculated set of clusters to start EM Clustering in R?

I have performed Hierarchical Clustering on a data set. I would now like to compare the BIC of the clustering methods. The process involves using the clusters you have determined to act as your ...
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Calculating BIC for Hierarchical Clusters in R

I'm performing Hierarchical Clustering Analysis on a set of data where I have a cohort of patients, and I am clustering them according to a set of variables. I have used hclust to perform the ...
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Hierarchical clustering in R - centroid linkage - problem with dendrogram heights

I have got a problem with understanding the hierarchical clustering algorythm, especially centroid linkage method. I have read many articles with description and they seems to be quite easy but I ...
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How to interpret contrasting information from the Variation of Information, Dunn and Rand Index for comparing clusterings

There are related questions but the answers don't seem to explain how to practically judge these measurements for non stats users. I have a dataset which I clustered with K=4 using hierarchical ...
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In cluster analysis should I scale (standardize) my data if variables are in the same units?

I am performing cluster analysis (k-means and hierarchical) based on multiple variables. Each variable is in percentage 0-100% and the sum of all variables is at most 100%. I see that in many of the ...
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Cluster analysis of variables or observations?

I'm very new to cluster analysis. In papers such as Richette et al.1 (which tries to see which concomitant diseases cluster together), authors first cluster the variables and then the observations (i....
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Using pcolor to visualize clusters (from Hierarchical Clustering in multidimensional space) or suggestions? [closed]

I have output from Hierarchical Clustering on my data which is multidimensional and hence difficult to plot and show cluster centers. My data points are regions within a larger image, and I was ...
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Clustering data that includes a categorical variable with many different levels

I'm looking to cluster data on apartments. I have the following variables for each apartment: Latitude Longitude Price Number of bathrooms Number of bedrooms Amenities (washer, gym, etc.) The ...
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How to cluster Categorical/Ordinal Survey Data

I have customer survey response data from Surveymonkey. I want to know what the best method would be for similarity analysis in order to create customer segments. Most of this data is categorical "...
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Accounting for repeat observations in k-means clustering

I am applying k-means clustering (i.e. kmeans function from the stats r package) to a distance matrix generated using ...
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42 views

Does it make sense to cluster asymmetric binary data with Ward's method?

I'm working with 104x42 data set where all variables are (asymmetric) binary (0-1). I've read that Ward's linkage method doesn't work theoretically properly with binary data beaucause it requests ...
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Should I use hclustvar instead of hclust to transposed data?

I am performing hierarchical clustering to a dataset with X variables (columns) and Y time points (rows) (kind of multivariate time series), where X << Y. I would like to cluster by the ...
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Computing Gini index and cross-entropy for a dendrogram

I am trying to calculate purity of clusters obtained through hierarchical clustering. I followed this tutorial here: Decision tree learning My question is: is computing these measures the same for ...
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Aggregating Cluster Analysis Results [closed]

I want to write something about cluster analysis. I have started to read something about it and I faced with a concept which is called ''Aggregating''. What does it mean for cluster analysis? Do I ...
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Hierarchical Cluster Analysis of 100 objects with 114 variables each

I'm intending to make a cluster analysis of 100 objects. I've read a couple of books and determined that a Hierarchical agglomerative procedure with Ward's linkage method should be used in my case. As ...
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Does k-means have any advantages over HDBSCAN expect for runtime?

I have recently learned about HDBSCAN (a fairly new method for clustering, not yet available in scikit-learn) and am really surprised at how good it is. The following picture illustrates that the ...
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silhouette score returns NaN [closed]

I'm computing silhouette_score from sklearn.metrics library in python, for hierarchical clustering. I'm computing this metric for few cuts of the tree (few options of number of clusters, K). For some ...
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Approximation of the number of neighbors a point has within its cluster in ROCK by Sudipto Guha

The paper (ROCK: A Robust Clustering Algorithm for Categorical Attributes) describes an agglomerative clustering algorithm based on the goodness measure for merging clusters $C_i, C_j$ $$g(C_i,C_j)=\...
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Cluster Groups based on overlap

I have the following data: ...
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How to do Hierarchical Clustering for Ordinal data-set in R?

I am trying to do Hierarchical clustering on a dataset where the columns are ordinal on the scale of 1 to 5. Based on Hierarchical clustering can be done using hclust() function. ...
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How does clustering improve a language model?

This article describes a hierarchical clustering algorithm which clusters the words within a vocabulary based on their similarity, in order to improve a language model (in the article, n-grams). How ...
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Intratumor heterogenity in ordinal scaled histology dataset? Cluster analysis for non independent observations?

I got my hands on a histology dataset and we want to analyze the heterogenity within brain tumors. My current but growing dataset contains 116 records from 29 patients. The tissues are dyed and ...
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Single Linkage Clustering with Manhattan metric

Say suppose we are having 5 data points with 3 attributes each ... (4,3,1) (2,1,5) (1,2,3) (2,3,1) .... Now let us build the distance matrix. If we do Manhattan metric then the cell corresponding to ...
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How to compare 2 clustering algorithm? [duplicate]

I have selected 'Nursery' data set from UCI machine learning repository and run 2 different clustering algorithm on, K Means and Hierarchical clustering. How should I compare these to algorithm to see ...
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Violating “compactness” in single linkage hierarchical agglomerative clustering

While I was studying Hierarchical Agglomerative Clustering in the book Elements of Statistical Learning in the chapter Unsupervised Learning, I came through the following : The statement The ...
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R: how to find cluster centroids with tsclust?

I have a time-series dataset and I am required to find similar clusters in the data. Based on my current knowledge and the requirements of my application, I used ...
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Meaning of internal cluster validation indices in hierarchical time series clustering

I'm working in R with the package dtwclust. When creating partitional clusters, I understand that internal cluster validation indices (CVIs) represent some measure of within vs. between cluster ...
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How can a population be grouped into a given number of groups, using their 3 choices of friends as input for grouping criteria?

I have a class of 92 medicine students with different friendship webs at hand. These people should be divided into 2 big groups for effective lecturing and the 2 big groups should be divided into ...
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Why SOM is better than clustering technique(e.g. hierarchical)?

I am using SOM for dimension reduction and visualization purpose (to put the same observations together). I am using kohonen r-package for the same. https://cran....
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Time series clustering: Is shape-based distance robust to non-stationarity? If not, is differencing a valid solution?

I'm working in R using the dtwclust package (Sarda-Espinosa 2018), and I want to cluster a set of time series hierarchically by the shape-based distance (SBD) metric (Paparizzos and Gravano 2015). Is ...
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110 views

What are possible reasons of clustering failure

I am applying K-means and hierarchical clustering to a dataset of gene expression profiles. Both of them fail, in the sense that by plotting the resulting clusters I cannot really identify people ...
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57 views

Unique Jaccardian Distance?

Hi I have a dataset that could be simulated using: ...
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2answers
209 views

Hierarchical Clustering: What is the difference between linkages and distance measures?

Clustering algorithm defines a particular distance (correlation or euclidean) and a linkage (which, strangely some books call distance - single, complete, average or centroid). Conceptually, ...
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How to cluster customers by their purchases

I have matrix with about 40 columns which are sales of specific products and about 15 000 rows. Each row is purchases of specific customer. The data consists of information about sales for 2 years ...
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273 views

Comparison between hierarchical clustering and principal component analysis (PCA)

I just read a article about the comparison between PCA and hierarchical clustering, but I cannot find the strengths and weakness of clustering compared Principal Component Analysis, what about other ...