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 of Variables around Latent Variables (CLV) over only qualitative data
I'm reaching out today because I have a concern regarding the clustering approach employed with the CLV method introduced by Vigneau and Qannari in 2003. I've noticed that this method is predominantly ...
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Clustering human evaluation
I am trying to figure out how can I evaluate my clustering methodology. I have gathered and processed some data such as:
I want to have several humans to put labels in column C, based on the top ...
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Design Effect in Cluster Randomised Trials
I want to understand why and how variance inflation factor is taken in account with the formula [1+(m-1)*ICC], where M= Size of clusters and ICC is the intracluster correlation.
As I have deduced till ...
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hierarchical clustering linkage
Just want to get verified with hierarchical clustering.
Let's assume that you want dissimilarity measure as euclidean distance.
Let's say that you have three clusters. Each cluster has many ...
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Multivariate Longitudinal Multi-level Model: What is the hierarchy structure?
I am interested in running a multivariate multi-level model with longitudinal data, and I'm having a hard time conceptualising the hierarchy levels.
My variables are:
Multivariate outcome: Quality of ...
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Combine two estimates of same variable
Suppose I know that $ A = 0.3 \cdot B + 0.7 \cdot C $
And I have these estimates:
$$ \hat A = A + \varepsilon $$
$$ \hat B = B + \zeta $$
$$ \hat C = C + \eta $$
For the sake of the argument, $ \...
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Hierarchial clustering given a list of banking syndicates
I have a list of banking syndicates (groups of banks), and I'm trying to do some hierarchical clustering on it to gather if there is some connection between them (e.g. if lots of syndicates share the ...
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In unsupervised learning, is a result of 2 clusters meaningful?
I used both agglomerative clustering and k-means on a dataset and see the results below. Result from agglomerative clustering was demonstrated with silhouette score while kmeans with inertia score. ...
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Calinski-Harabasz score as a validity index for hierarchical clustering with distance matrix
I have a distance matrix that I want to performed hierarchical clustering with, and find the optimal number of clusters by maximizing the Calinski-Harabasz (CH) score. However, I only know how to ...
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Question about Color Histogram [closed]
In the description of the Color histogram, it is stated that 25 bin is set for each color channel, the dimension is n = 75 (RGB 3 channel * 25 bin), and then L1 Normalization is performed. Does this ...
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Distance measurement methods used in Hierarchical Clustering
In Hierarchical Clustering, what are the distance measurement methods used? Are different measurement methods used depending on the purpose?
If performing Hierarchical Clustering for Region Proposal, ...
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Inconsistent cluster indices using hierarchical clustering for time series data
I am currently trying to spatially cluster data that is ordered on a grid. Each point has x and y coordinates as well as a measurement value. These features come from a time series where I analyze ...
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Is "ward.D" a good agglomeration method in R?
I need to do clustering on a large scale file (~12M rows, 18 features + id index). As a first step, i tried different algorythms in Python with a test sample (40k rows) which gave results (clearly ...
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P values of coefficients from ClusterBootstrap GLMs
I am using the following data
https://docs.google.com/spreadsheets/d/1ovl8oQnIi_uApVCo93BN_UOUY3F1YoKw/edit?usp=sharing&ouid=117026321594556045652&rtpof=true&sd=true
and the ...
Hannah Harder
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Should similarity matrix must always be converted into a dissimilarity matrix for hierarchical clustering?
Background
Hi all, I need some clarification on my approach if it's correct or not. I have a matrix (M_ij) with user ratings of images. The users (i) are on the horizontal axis and the images (j) are ...
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Standardize agglomerative feature clustering across samples or features?
I know that typically, one has a feature matrix of n samples by m features. Let's say I have a matrix X in this format. If I was going to perform hierarchical clustering on the samples, I know I ...
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How to automatically choose the optimal number of clusters for a hierarchical clustering dendrogram? (R or Python)
I have a product substitutability matrix, where each cell has a number between 0 and 1 to represent how substitutable (i.e. how similar) the two products are.
I then apply hierarchical clustering to ...
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Finding the nearest point to a given set of points [closed]
I am trying to build an auto-suggestion logic which looks at currently selected items and recommends a list of items to select the next item from.
I can formulate the problem thus:
Given a set of ...
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Clustering of known clusters: how to cluster by patient?
I have N patients. Each one of them performed T tasks, and each task if performed M times. For each task, I get some measurements from which I extract a vector of features. I therefore have T*M ...
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Cluster analysis after factor analysis: What distance measure to use?
I use factor analysis on a set of 15 survey questions (likert scales).
Using the predict command (in stata) I make 5 factors.
Subsequently, I want to use cluster analysis to see if there are "...
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What are the downsides of using euclidean distance for hierarchical clustering of a correlation matrix?
Apologies if this has been answered elsewhere, but I couldn't find any answers discussing this specific question.
I am lacking some notion on clustering using euclidean vs correlation distance, when ...
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Unsupervised learning: How to identify differences between clusters?
I'm learning about unsupervised learning and I tried to use KMeans, AgglomerativeClustering and DBSCAN on the same datase. The result was ok, they seems to work fine according silhouette_score() ...
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Choosing the best clustering algorithm and evaluating the results
I'm trying to separate my data into clusters using the k-means algorithm and the hierarchical algorithm, choose which algorithm fits my data the best, and evaluate the results. However, all of my ...
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Are there algorithms to cluster Graphs, not just cluster nodes in a graph?
I am wondering if there are algorithms to cluster graphs; what I meant is to cluster many graphs, not cluster the nodes in a graph.
For example, we have N graphs, G1, G2, G3, .....GN. Then we can ...
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Negative gap statistic interpretation for cluster analysis
I am trying to perform a cluster analysis on a dataset. The plot of clusters vs. gap statistic is below. I do not know how to interpret the decrease of the gap statistic and its values which are ...
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Feature Scaling in Hierarchal Clustering
I know that feature scaling is always a requirement for clustering algorithms. Currently I am implementing hierarchal clustering on this dataset, I will use only the annual income and the spending ...
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How to choose a heatmap distance and clustering method (with ecological data)?
I'm interested in learning about the various methods for clustering heatmaps in the context of ecology (specifically single species counts, presence/absence, % coverage and continuous environmental ...
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SPSS: how to calculate nearest neighbor from k-means centroids
the subject of my problem is related to cluster analysis. Specifically, with SPSS I am conducting a cross-validation procedure based on splitting the sample data into two independent halves (subsample ...
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Using Ward's method on a dissimilarity matrix of Gower distances
I have a question regarding Wards method of hierarchical clustering.
I used Gower Distance to create a dissimilarity matrix from an event log. I want to agglomerate it with Ward's method.
Lets suppose ...
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How to interpret bootstrapped Hclust
I have conducted a bootstrapped cluster analysis on data similar to the following:
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What graph is best suited for this data? (and how can I produce it in R)
I have this df object (9x19),
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Clustering Algorithm with Continuous and Binary Variables
I am creating a clustering analysis with both Continuous and Binary variables and am wondering
What type of model is best for these cases
How should I scale my data. Should I only scale Continuous ...
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Comparing Clusters of different data sets
I am trying to see how stable the hierarchical clustering is of return of stocks using different periods. I have the information of one year, and I divided the periods with a two month rolling window.
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finding differences in clusters between two populations
I'm looking for papers that deal with the problem of finding clusters that are different between two populations.
Suppose I have a retail website, and I know the clusters of my visitors. Now, I launch ...
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Distance function that captures both circular and "appear as line" clusters [closed]
based on what I know in k-mean clustering, if i use single linkage distance it can capture clusters of thread shapes but it is not suitable for capturing circular clusters.
Also If we use complete ...
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Multilevel/ Mixed Model / HLM Centering Interactions Level 1 and Level 2 Cross-Level
I am having some trouble with the literature on the correct model specification for my question.
Here is the setup:
I have a multilevel model with a variety of variables at level 1 and a single level ...
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Can I run a Manova after conducting a cluster analysis?
So my study intends to conduct a cluster analysis using 2 variables (RP and AP).
I intend to find four clusters (AC, BC, CC and DC).
I would then like to examine differences in education, height, age, ...
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Comparing clustering methods based on internal Cluster Validity Indices
I have used the R package dtwclust to generate clusters for more than a thousand time-series objects.Since I did not have any prior information on the number or validity of clusters, I used a suite of ...
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Clustering similar words in different sets
Suppose I have $N$ sets as follow:
$$S_1 = \{a_1,a_2,\cdots,a_n\}$$
$$S_2 = \{b_1,b_2,\cdots,b_n\}$$
$$S_3 = \{c_1,c_2,\cdots,c_n\}$$
$$\vdots$$
elements of each set (i.e., $a_n$, $b_n$, $c_n$ and etc)...
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Should mixed-data (incl. weights) be pre-normalised/scaled/standardised before computation of a distance matrix for hierarchical clustering?
should i scale the mixed data type before i perform hierarchical clustering?
A question very similar to mine was asked above however it wasn't quite answered...
For background: I am using a large ...
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how to calculate the missclassification rate/ Accuracy rate for clustering?
I am working with cluster models. I tried to find an accuracy rate/misclassification rate manually. I found an example that confuses me.
The example can be accessed from here. I think the author find ...
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Approximately Unbiased P-value vs Bootstrap Probability: which one should i choose?
Some references first:
How is approximately unbiased bootstrap better than a regular bootstrap with regards to hierarchical clustering?
Suzuki et al. 2004 https://www.researchgate.net/publication/...
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Distribution of conditional posterior for Gibbs sampling
The following is a description of how the authors (Yongning Wang & Ruey S. Tsay) of this (2019) paper Clustering Multiple Time Series with Structural Breaks want to perform Gibbs sampling to ...
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Is there a hypothesis test for members of hierarchical clustering clusters?
Suppose my data has $N$ observations, and each observation may be classified into one of three factor levels $\{A, B, C\}$. Using a vector of attributes for each observation, $\{x_1, x_2, \ldots, x_n\...
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Why not link features instead of selecting them - Clustering
Currently, I am working on customer segmentation using their purchase data. I plan to use clustering techniques.
So, my data has below info for each customer (9 features and 1 id field)
Now I am ...
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Hierarchical clustering output 99% belongs to a cluster group
I've just done a clustering analysis using hierarchical clustering analysis in Python but the result is not what I expect. Most of them (483/485) belongs to group 1 and the rest to group 0. Is there ...
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Distance between two clusters after their joining in centroid linkage
For a distance between two clusters A and B of objects given by $d_{AB}=\left \|{m_{A}-m_{B}} \right \|^{2}$ , where $m_{A}$ is the mean of the objects in cluster $A$, show that the formula ...
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Intuitive explanation of Ward's method
I got this explanation of the Ward's method of hierarchical clustering from Malhotra et. al (2017), and I don't really get what it means:
Ward’s procedure is a variance method which attempts to ...
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Why does single linkage create loose clusters when it uses smallest distance between two points?
The definition of single linkage says: In single linkage method, the distance between two clusters is defined as the minimum distance between two data points in each cluster.
However, different ...
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How to Determine Cluster Count with Hierarchal Clustering
I have analyzed the following Data set in R using hierarchical analysis, and plotted the results. Ive been asked to find and highlight the number of clusters present, but how exactly do you determine ...
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