Questions tagged [ward]
Ward's method is one of "linkage rules" in hierarchical agglomerative cluster analysis. In Ward's method, those two clusters are chosen to merge at each step that would yield the lowest increase in error sum of squares.
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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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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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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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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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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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Objective for Ward's agglomerative clustering
As far as I understood the original article (Ward, J. H. (1963). Hierarchical grouping to optimize an objective function), Ward proposed the following criterion for agglomerative clustering.
In each ...
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How can I cluster plant biomass and grain weight for different plant varieties using Ward's method based clustering?
I have plant biomass and grain weight data for different plant varieties which I now need to cluster. Do I need to define the number of clusters if using Ward's method and Squared Euclidean distance ...
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How to validate clusters after calculating Gower distances and Ward's clustering in R
I am trying to apply Ward's clustering on a mixed types dataset, and wanna explain what I did (maybe helpful to others), and I have some questions regarding this analysis, mainly how to validate my ...
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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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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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Difference between Ward hierarchical clustering and K-Means for classification
I have a dataset where of socio-demographic features of a population (expressed as percentages over the total population of the municipality: e.g. 12% of freelancers, 5% of unemployed etc.), each ...
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Why is only Euclidean distance allowed to be used for Ward's method? [duplicate]
Using scipy, I noticed that I am allowed to use only Euclidean distance for Ward's method.
Is it because Ward's uses Error Sum of Squared?
What if I use Ward's method with cosine similarity?
Cosine ...
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Hierarchical clustering Ward's method. The missing rationale in derivation
The Ward's method is taking distance as how much the sum of squares will increase when we merge them.
$d(u,v) = \frac{|u||v|}{|u|+|v|}{|m_u-m_v|}^2$
Please refer to Page 3 of link below.
https://...
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Difference Between Cubic Clustering Criterion, Silhouette Score, and Calinski Harabasz
I am clustering a mixed geological data set containing numeric (pump pressure, bit speed, mud temperature), nominal (presence or absence of a specific stones), and ordinal data (relative concentration ...
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Where does ward.d2 and cubic clustering start misclassifying for small sample sizes?
Given
Two univariate Gaussian distributions with unit variance and means and separated by distance 'dx', from which samples of size N are drawn from each distribution.
Find
the minimum value of dx ...
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How do I identify the object most 'typical' of a hierarchical clustering analysis?
I have used Matlab to carry out hierarchical clustering on habitat types. Each habitat has a set of physical characteristics that are quantifiable. Using a set of 50 habitats with 5 variables per ...
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Step-by-step: Ward's method for calculating linkage
I'm trying to use Ward's method to calculate linkage for hierarchical agglomerative clustering with the data points below:
$$a=(0,0)$$
$$b=(1,2)$$
$$c=(3,4)$$
$$d=(4,1)$...
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Applying Ward's method for calculating linkage
For an assignment, I have used iPython to create the dendrogram below, using Ward's method and Euclidean distance, from the following data:
$$a=(0,0)$$
$$b=(1,2)$$
$$c=(3,4)$$
$$d=(4,1)$$
$$e=(2,2)$$
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cluster centers very similar while dendogram shows high merge cost
I'm running a hierarchical cluster analysis (ward method, euclidean distance in the standardized variable space using scale function) and by looking at the ...
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Why does the row order of the sequences in TraMineR influence clustering results (Wards method)?
We have a large sample (44,933 sequences each of potential length 35) with 9 states. We create a standard dissimilarity matrix:
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A high cophenetic correlation coefficient but dendrogram seems bad
I have 2 results for the same dataset. One is hierarchical clustering using Ward's method and I got 0.75 cophenetic correlation coefficient. The second is average method and I got 0.91 cophenetic ...
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Using Ward's method for clustering and Dice's similarity coefficient for binary data
I am trying to isolate the most similar groups from a set of binary variables while minimizing variation within the clusters.
Is it valid to use Ward's method for clustering and measure similarly by ...
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How to interpret the numeric values for "height" in a dendrogram using Ward's clustering method
I am a biology student investigating a new method of creating a dichotomous identification key. I have created a dendrogram using data I have collected from a survey on how people rate how similar ...
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Gower's dissimilarity measure and Ward's clustering method
I have read some threads on this website saying that it is not OK to use Gower's dissimilarity matrix for Ward's clustering algorithm.
I have mixed type variables, first I had a dissimilarity matrix ...
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What algorithm does ward.D in hclust() implement if it is not Ward's criterion?
The one used by option "ward.D" (equivalent to the only Ward option
"ward" in R versions <= 3.0.3) does not implement Ward's (1963)
clustering criterion, whereas option "ward.D2" implements ...
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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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Which similarity coefficient should I use with Ward linkage?
I just attempted implementations of Ward linkage and UPGMA linkage, as well as Pearson and Euclid similarity coefficients. To my surprise, both similarity coefficients gave the same clustering with ...
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Is there any way to know if my clusters are meaningful or meaningless? [duplicate]
Possible Duplicate:
How to tell if data is “clustered” enough for clustering algorithms to produce meaningful results?
I have used hierarchical clustering, e.g, Ward's method, single,...
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Gower's (dis)similarity index
I would like to ask a question about Gower similarity/dissimilarity index.
Is it ok to use the Gower dissimilarity measure with Ward linkage clustering?
I was reading that the Gower similarity index ...
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How does "ward" clustering (in R's hclust function) work?
A simple example:
plot(hclust(dist(c(1:3)),method = "ward"))
I would like to know which calculations (in R) can reproduce the distance of 3 from {1,2} to be
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Is it ok to use Manhattan distance with Ward's inter-cluster linkage in hierarchical clustering?
I am using hierarchical clustering to analyze time series data. My code is implemented using the Mathematica function DirectAgglomerate[...], which generates ...
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