# 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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### How to select a clustering method? How to validate a cluster solution (to warrant the method choice)?

One of the biggest issue with cluster analysis is that we may happen to have to derive different conclusion when base on different clustering methods used (including different linkage methods in ...
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### Choosing the right linkage method for hierarchical clustering

I am performing hierarchical clustering on data I've gathered and processed from the reddit data dump on Google BigQuery. My process is the following: Get the latest 1000 posts in /r/politics ...
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### How to interpret the dendrogram of a hierarchical cluster analysis

Consider the R example below: plot( hclust(dist(USArrests), "ave") ) What exactly does the y-axis "Height" mean? Looking at North Carolina and California (...
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### Using correlation as distance metric (for hierarchical clustering)

I would like to hierarchically cluster my data, but rather than using Euclidean distance, I'd like to use correlation. Also, since the correlation coefficient ranges from -1 to 1, with both -1 and 1 ...
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### How to understand the drawbacks of Hierarchical Clustering?

Can someone explain the pros and cons of Hierarchical Clustering? Does Hierarchical Clustering have the same drawbacks as K means? What are the advantages of Hierarchical Clustering over K means? ...
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### Clustering -- Intuition behind Kleinberg's Impossibility Theorem

I've been thinking about writing a blog post on this interesting analysis by Kleinberg (2002) that explores the difficulty of clustering. Kleinberg outlines three seemingly intuitive desiderata for a ...
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### Hierarchical clustering with categorical variables

Can categorical variables be used in hierarchical clustering? I have heard only continuous variables are used, but have seen people discussing categorical variables may / may not be used as well. ...
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### Choosing the number of clusters in hierarchical agglomerative clustering

I have a set of points that I want to cluster into groups according to a number of features computed. I have distance matrix containing the distances between all different pairs of points. I have ...
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### How to interpret dendrogram height for clustering by correlation

Given the following data frame: ...
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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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### Do I need to remove duplicate objects for cluster analysis of objects?

I am doing a cluster analyis and I was wondering whether it is possible to remove duplicates from the data set - in order to increase performance. I work on tables where objects are in rows and ...
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### What is the interpretation of eps parameter in DBSCAN clustering?

I want to cluster lat-long data such that all clusters formed will have radius<=1000 meters Questions What is the actual meaning of eps parameter? Please given an example. Will setting eps=1000 ...
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### Does a distance have to be a "metric" for an hierarchical clustering to be valid on it?

Let us say that we define a distance, which is not a metric, between N items. Based on this distance we then use an Agglomerative hierarchical clustering. Can we use each of the known algorithm (...
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### Hierarchical clustering of correlation matrix

I have a correlation matrix of 8,854 * 8,854 size. These are Pearson correlation coefficient values in the matrix. I want to perform Hierarchical clustering and create good resolution images like I ...
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### Can sub-optimality of various hierarchical clustering methods be assessed or ranked?

Classic agglomerative hierarchical clustering methods are based on a greedy algorithm. This means that they (many of them) are prone to give sub-optimal solutions instead of the global optimum result, ...
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### Hierarchical clustering with agnes - how to cut the tree?

I am working on a data.frame with both categorical and metric variables ...
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### Best practices in the selection of distance metric and clustering methods for gene expression data

I have been reading about this on various channels including here and Stack Exchange, but I'm still not sure how to choose the best approach for clustering gene expression data. As a Ph.D. molecular ...
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### Choosing the number of clusters - clustering validation criterions vs domain theoretical considerations

I often face the issue of having to choose a k number of clusters. The partition I end up choosing is more often based on visual and theoretical concerns rather than quality criteria. I have two ...
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### Pooling levels of categorical variables for regression trees

I have a data set I would like to do a regression analysis for. There are many features of both categorical and continuous types. One of the categorical features has many (>75) levels so this is an ...
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### Why are the cluster analysis results using raw data the same as the ones using PCA scores?

I have read around a lot and tried different ways to carry out my cluster analysis. In the first case, I have carried out a hierarchical cluster analysis on my raw data (200 watersheds and 16 ...
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### K-Means Cluster has over 50% of the points in one cluster. How to optimize it?

I am running a clustering algorithm in Spark and I have to choose between K-Means and Bisecting-Kmeans. However the only thing that differes between the two is the runtime because the performance is ...
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### Is there an advantage to squaring dissimilarities when using Ward clustering?

Is there a reason to prefer squaring or not squaring the dissimilarities when clustering with Ward's method? The question is motivated by the following statement in the documentation for R's ...
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### Conditional intraclass correlation (ICC) from a linear mixed model as evidence for test-retest reliability?

In my experiment with two conditions (between-subjects design), participants completed a single-item scale three times: (1) before the experimental manipulation, (2) after the experimental ...
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### Determining similar users from hierarchical clustering

I use hierarchical clustering to cluster users which are similar to each other based on a Jaccard coefficient. I have now coded a solution to extract similar users based on hierarchical clustering: ...
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### Increasing multicollinearity in multilevel/hierarchical modeling?

I have a linear model with response variable $\textbf{y}$ and explanatory variable matrix $\textbf{X}$ for which coefficients $\textbf{b}$ are physically meaningful and worth estimating: \begin{...
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### How to assign existing cluster numbers for future data, using hierarchical clustering algorithms?

Assume we have some good clusters from some clustering algorithm and we want to assign the cluster numbers (labels) to future data (= to enrol new data points into the existing clusters, if to word it ...
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