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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Handle outliers in clustering
I’m working on a cluster analysis of Italian provinces based on three fire-related indicators: total burned area (ha), burned area per fire, fire density.
Because these variables are measured on ...
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Selecting best method for calculating dissimilarities between sequences with TraMineR
I'm completing a sequence analysis to examine the progression of mental illness diagnoses for people who get diagnosed with a psychotic disorder. Here is some dummy data similar to what I'm working ...
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Hierrachical Clustering in R - how to make a data set with row names [closed]
I have a data set on underground water mineral content measured along a river basin at three locations: Upper, Middle and Lower. The measurements are on 14 items and two unmeasured items, Section and ...
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Am I using the correct clustering method?
I have a dataset of developing bird vocalizations. In order to annotate song syllables during early development, I am doing the following:
Creating a matrix with pixel values of all my syllables over ...
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Rotated loadings as input to hierarchical clustering
How do we feed the rotated loadings obtained through varimax rotation using psych package to hierarchial clustering in the FactomineR package (HCPCC())? I want to use the rotated components instead of ...
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ICC values the same for different null models with different independent variables
I have 25 variables. I then fit 25 null models (without predictors). Their responses for the dependent variables differ, however, the number of observations are the same and grouped by the same number ...
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What is this algorithm for identifying an optimal number of clusters in HCA?
I'm using some software that does (among other things) hierarchical clustering and automatically chooses a number of clusters to use if one is not specified. I wanted to know what method it is using ...
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Cross validation: Multilevel model with the research question, what are the factors that shape practice?
I was advised to use Multilevel modeling for my data analysis on this platform. The model speaks to the data structure and my study's theoretical framework. I thus find it suitable.
Here is the model ...
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Should I flip (negate) anticorrelated variables in hierarchical clustering?
In hierarchical clustering, I have one variable that seems to be coded the opposite direction to the others. It has a negative correlation with a majority of the other variables. (eg var 3 below)
I ...
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What statistical tests can I use in R to ascertain the statistical significance of clusters obtained using DIANA (DIvisive ANAlysis Clustering)?
I have a data set of cuticular hydrocarbons (CHCs) from 60 samples of aphids collected across mid, early and late activity season on three different plants species that they fed on. The CHCs can ...
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About adding random effects in Multilevel (HLM) analysis
I am doing regression analysis in HLM. I am wondering whether random effects should be added in this process.
Let me ask a question using a famous example. LV1 is a student and LV2 is a school. LV1 ...
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calculation of the C-index clustering [duplicate]
Can anyone give me an example of working on the C-index clustering validity test, but calculating manually??
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Hierarchical Clustering Using Mutual Information
I am interested in Hierarchical Clustering Using Mutual Information. Asking the ChatGpt, I got this:
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Evaluate hierarchical clustering with partial ground truth
I am performing hierarchical clustering, and I need to decide which agglomeration method to use.
While I don't have a ground truth, I know that some datapoints should be closer together: for example, ...
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Hierarchical Clustering with Large Datasets
I am currently aiming to perform hierarchical clustering for the purpose of customer segmentation. My dataset consists of 217,000 instances with 12-15 features. However, due to memory issues when ...
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