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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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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Does the distance matrix have to be symmetric for a cluster analysis using Ward's method?

Does a distance matrix used in a cluster analysis need to be symmetrical? My past experience with cluster analysis usually involved a lower triangular distance matrix but a recent method I came across ...
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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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Are height numbers meaningful when interpreting a cluster dendrogram? (Bray Curtis & ward.D2)

When interpreting a dendrogram produced with a Bray Curtis dissimilarity matrix, do the height numbers have more meany than just relative distance between clusters? Based on the dendrogram below and ...
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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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Strange cluster assignment at edge of cluster

I'm experimenting with HDBSCAN and am encountering some results that I don't fully understand. Mainly about a datapoint that gets assigned to another cluster than I would expect it to be. Hopefully ...
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Compare hierarchical clustering results with different imporance scaling

For an assignment at university, I am using hierarchical clustering of a dataset of 5 different parameters. The parameters all have different magnitudes, so I standardized the data using a z-score ...
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Want to understand dendogram's basic expample from scipy website

I like to understand, how the given array leads to corresponding points in x and y coordinates? ...
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Python Implemenatation of SPSS's Two-Step Clustering

I want to perform a clustering on data with ~40 binary features. I was recommended the two-step approach by Chiu et al.. They basically use a BIRCH variant to determine pre-clusters and then perform ...
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Similarity between datasets A and B where B is a subset of A

I have two datasets A and B, and for each entry in both datasets I have a mixture of ordered and unordered categorical variables such as gender, age (integral value) and date. It is believed that ...
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Breaking Tie with Ward's Method Hierarchical Clustering

Viewing the set of single-feature observations below, I think its obvious that the appropriate Euclidean distance-based (e.g., Ward's method) number of clusters is 3. ...
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Testing individual effects on aggregate dependent variable

Please help! How do you test the effect of individual observations on an aggregate dependent variable? Can HLM or some other multilevel mixed effects model help me test this? I know these models can ...
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Optimal number of clusters in gene expression data

I'm clustering genes on gene expression data. Here's a hierarchically clustered heatmap using ward linkage and Euclidean distance It clearly shows there are 5 or 6 clusters. Now when I evaluate their ...
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Does it make sense to use variables' product as a new variable in a clustering procedure?

I'm trying to separate different groups based on values from width and length using k-means and hierarchical clustering. My question relates to the possibility of using the area — measured as width * ...
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Are the distances on a hierarchical clustering dendrogram in the same units as the input distance matrix?

I use Aitchison distance as the input to a hierarchical clustering dendrogram. I started labeling and interpreting the dendrogram but wasn't sure about a few aspects: Are the vertical distances on ...
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Interpretation of the height of a dendrogram and intra/inter deviance corrispondence

I am practicing hierarchical clustering and I am having doubts about the interpretation of dendrogram height. Let's take the code in example with points (1,1), (2,2), (5,5), (9,9), (10,10), and (13,13)...
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Hamming distance, ignoring matching 0

I have a dataset with about 800 observations, each with about 2000 boolean variables. I would like to cluster the observations. I am using scipy in Python. For a (dis)similarity measure I've chosen ...
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Agglomerative hierarchical clustering of observations with binary variables

I have a dataset with about 800 observations, each with about 2000 boolean variables. I would like to cluster the observations. Now, I'm pretty new to all of this so I hope you'll bear with me. My ...
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When can I say there is no clusters?

I am trying to do cluster analysis for a very small data set (<100) in higher dimensional feature space. I tried K-means and Hierarchical clustering, but I found no 'elbow' and also the silhouette ...
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Select number of clusters k-means

I have a practical question. I am trying to select the number of clusters in k-means clustering and I have tried a Silhouette analysis, an elbow plot looking at the residuals, and a hierarchical ...
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Constrained Clustering via Distance-Based Multivariate Regression Trees in R?

I was wondering if distance-based multivariate regression trees (or distance-based multivariate random forests) are implemented any R package? De'ath (2002) describes multivariate regression trees ...
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Understanding Bayesian Hierarchical Model in Practice

I have a Bayesian hierarchical model with datapoints $y_{ij}$ which are samples from distributions with parameters $\theta_j$. For each distribution parameter $\theta_j$, there are $n_j$ datapoints ...
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Distance measures for row ordering of a sparse heatmap with discrete row data

I have a list of protein indexes. Each protein can be either (i) a feature component F in a feature group G (in which case the index is included in the list) or (ii) a background component B (in ...
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Best distance measure for cluster analysis of time series data with a circular variable

I'm doing hierarchical clustering on a set of time series (say 21 time series of 400 time points), however the variable I want to cluster is a circular variable, i.e. a directional vector between 0 ...
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Unsupervised Clustering with Extra Information

I have a task to cluster an almost entirely unlabelled dataset. After reading the literature on semi-supervised clustering, I have not found any algorithms that suit my very particular needs. ...
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Clustering large yearly, (presence/absence) dataframe

I have a data frame of 500,000x23 dimensions. The data is binary, representing presence or absence. The data follows identified trees through time (23 years) and looks at whether the tree is present ...
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Clustering and data scaling

I have a dataset with 5 questions, which are scaled 1-10 and income variable, which is nominal. Should I standardise all variables with min/max scaler, or convert income to 1-10 scale? What is the ...
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How to deal with visually overlapping clusters

I have done hierarchal clustering (average) and silhouette method shows 6 as the best k. However visualising I see that most of the clusters are overlapping. Any way to deal with the overlapping ...
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Negative silhouette width in clustering

I have some clusters having observations below 0 Si (showing that they are not in a right cluster I assume). I am doing hierarchal clustering on a binary data. One of the solutions I found was ...
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What is the optimal number of clusters?

I am doing a cluster analysis with agglomerative hierarchical clustering on my asymmetrical binary data. For finding the number of clusters, I tried all three of the most mentioned methods (Elbow, ...
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Clustering multivariate binary data

I want to use a clustering algorithm which can catch the following within a multivariate binary dataset. In the sample below, since class 1 and 2 appear twice within column A and B they will form a ...
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PCA or Drop high correlated variables for clustering

I am performing clustering on mixed data type. I have few features which are high correlated. We generally use PCA before clustering and reduce the feature space, as its a mixed data I have used FAMD ...
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Definition and Taxonomy of Seasonal Time Series

I want to categorize a large number of time series into non-seasonal and seasonal divide the seasonal ones into a small number of subgroups by type of seasonality Are there any formal definitions/...
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How can I clustering from an hourly time series of winds for various stations?

I need to make a classification of different meteorological stations based on hourly time series of winds in their u and v components date site u wind v wind 2018-01-01 0:00 ACO -0.52 -1.45 2018-01-...
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How do I hierarchically cluster column containing multiple categorical variables in r?

I'm trying to do some hierarchical clustering on some movie data and ran into a conceptual issue with a column containing the movie genres. The column will code genres as a string of integers ...
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Agglomerative clustering by groups

For the majority of tutorials and examples of agglomerative clustering on the internet I find that the methodology is applied to individual observations, in one example I found that they used this ...
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Hierarchical clustering detection with categorical variables in R with missing data

I am trying to find a hierarchical pattern in categorical data that I have. The data is sort of like this (as I am not allowed to use the actual data, I created a similar problem that follows my own ...
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Unsupervised Clustering of large multi-dimentional data

Hello I am a machine learning newbie. I need some help with unsupervised clustering of high dimentional data. I have data with over 15 dimensions with around 50 - 80 thousand rows. The data looks ...
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Do we check for association between categorical variables before clustering mixed-type data?

I am clustering mixed-type data using hierarchical clustering and the Gower measure. My question is: Do we have to check for association (dependence) between categorical variables (e.g. using chi-...
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Aggregation followed by categorization or vice versa?

For unsupervised classification purposes using several variables, I need to categorize one continuous variable into two classes, particularly, using Z-scores. The issue is that the continuous data ...
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How test the differences between clusters in R?

After performing an Hierarchical Clustering on Multiple Correspondences Analysis, I want to test the differences between my variables amongst the clusters. The goal is to see which variables is more ...
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How to look into Agglomerative linkage matrix to find optimal number of clusters using python

I am generating the linkage matrix on 73k data-points. The objective is to find the cut-off point by visualising the distance ...
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Hierarchical Clustering Validation Statistics using FactoMineR [closed]

I'm running the HCPC function in the FactoMineR R package to perform hierarchical clustering on FAMD. I was able to run the HCPC function to generate clusters without any difficulty, but I was having ...
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When doing hierarchical clustering, do we need to exclude variables with high correlation?

I have one question regarding the hierarchical clustering. I personally have used this hierarchical clustering methods a few times, but did not apply it to the protein level data before. What I am ...
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Clustering Psychometric Survey Data

I have created a 15 question survey to understand the financial preferences of people. It asks questions like- 'How comfortable are you making financial decisions?' with generally 4 or 5 options ...
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Do I correctly apply hierarchical clustering and K-means on the resource-selection-function values?

I'm trying to find the best way to classify bivariate point patterns in spatstat according to the relationship between two point species: Point pattern ...
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Weighted metric for mixed binary (decomposed) data?

I have a large dataset with mixed type of data (example): Age Price Town Size Interests Small Middle Big Traveling Cooking TV 21 0 1 0 0 1 1 1 34 100 0 1 0 0 1 0 81 200 0 0 1 1 1 0 54 0 0 0 1 1 ...
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Why spatially overlapping clusters?

I would like to know why sometimes overlapping clusters exists in a clustering analysis? For example, the picture below shows the result of HCPC from Factominer. It is strange and I can not find a ...
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