Questions tagged [gower-similarity]
Gower coefficient is a similarity measure for mixed type data (quantitative, binary, categorical). 'Gower distance' refers to this tag too.
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Approximate Gower's dissimilarity measure
I have a very large dataset with mixed-type variables. When I apply the Gower's dissimilarity measure to obtain the distance matrix, it is running out of memory. Due to the large size of the data, it'...
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When using a gower dissimilarity matrix for use in dbscan clustering, the bools still perfectly separate the clusters
I am working on a clustering analysis where my data is a mix of bool and numeric. From research it looks like one should not do a simple kmeans with mixed data types since the extreme end of scaled ...
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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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Clustering method for Gower distances [closed]
I am having a mixed data type and I want to implement cluster my data set into 3 clusters. Because I have mixed data I have to compute gower distance as part of a distance matrix.Now that I have this ...
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Options for Clustering Analysis with Numeric & Nominal Data with Gower Distance
I am working through some cluster analysis (trying to propose new item types for various clusters). I have data that has both numeric and nominal features. After creating dummy variables for all ...
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How to use Gower's Distance with DBSCAN algorithm in Python [closed]
I have been researching about using DBSCAN with sklearn in python but it doesn't have Gower's distance metric built in. All the other implementations are in R in this community.
I'm using a dataset ...
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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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Gower Distance and PAM algorithm with Random Forest for Variable Selection
I am currently working with cluster analysis and am trying to create clusters based on the important variables. My data consists of both categorical and continuous variables thus I have used the ...
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Clustering Data Using Gower and Kmeans
I am trying to do clustering on my data which consists of both categorical and continuous variables. I have some questions which I would like to ask:
I am going to use the Gower Distance measure to ...
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Is one-hot encoding and standardization of data equivalent to Gower's distance?
For clustering and other techniques for mixed data (numerical and categorical), Gower's distance is usually more preferred than Euclidean distance because the former computes distance differently for ...
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How to use Gower's Distance with clustering algorithms in Python
I am trying to cluster by dataset with mixed features using k-means. As a distance metric, I am using Gower's Dissimilarity. I want to ask 2 things:
-Is k-means an appropriate algorithm that can ...
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Gower's (dis)similarity: How are numeric values scaled?
I am trying to understand the concept of Gower's (dis)similarity measure and I have problems to understand the scaling method for numeric variables.
Are numeric values just scaled between 0 and 1 ...
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How Gower's dissimilarity handle missing values in numeric columns?
I would like to ask a question about Gower dissimilarity, I was wondering how Gower measure handle missing values in numeric columns, especially that Gower standardized each column based on the range ...
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Gower's Distance issue
So, I'm relatively new to using Gower's distance to do cluster analysis. I've done some research on this for a little while and like the fact it can incorporate categorical variables. To get a better ...
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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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Gower distance with R functions; "gower.dist" and "daisy"
I have 9 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I know that the Gower distance is a good metric for datasets with mixed variables.
I tried both daisy(cluster) and gower....
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Gower distance with R
I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I know that the Gower distance is a good metric for datasets with mixed variables.
When I use daisy function in cluster ...
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K-medoids clustering with Gower distance in R
I have both numeric and binary data in my data set with 73 observations.
I read a lot about which distance metric and which clustering technique to use especially from this web site.
I decided to use ...
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How does the Gower distance calculate the difference between binary variables'?
I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. ...
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How to compute the centroid of a cluster for Gower distances
I'd like to assess how scattered a cluster of binary vectors $X_j$ is, and as I understand the conventional way for doing this is:
$$
S = \frac{1}{T} \sum_{j}^{T}\|X_j-A_j\|_p,
$$
where $A_j$ is the ...
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How does Gower distance work with free text?
The Gower distance measure is a good measure for mixed-type data (i.e., data attributes can be qualitative, categorical, ordinal or binary). But can data attributes be free-text (e.g., names of people)...
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Gower distance and MDS: How to determine which variables count?
I have morphological data from two different determined groups (It and Nd), where the variables are heterogeneous (continuous, ...
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Cluster many thousands observations (mixed variable types). Cluster subsample and then classify the rest observations?
I'm trying to run a cluster analysis on a large dataset (70k+ observations to cluster) with mixed variables (numeric, ordinal, binary and nominal). I don't think I can create the distance matrix using ...
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Determining number of clusters with SSE scree plot with Gower's coefficient of similarity
I am researching cluster analysis, and I am interested in variables that are both categorical and continuous, for which I have read that a Gower's similarity coefficient is a good proximity measure. I ...
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In cluster analysis, can you use Gower's coefficient of similarity with a k-means clustering method?
I am researching cluster analysis, and I am interested in variables that are both categorical and continuous, for which I have read that a Gower's similarity coefficient is a good proximity measure. I ...
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Manual computation of Gower's similarity coefficient
There is an example on the computation of Gower's similarity coefficient on the page,
Gower's similarity coefficient
I am trying to work out the similarity manually between patient 1 and 2, however ...
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Confidence intervals around a centroid with modified Gower similarity
I would like to obtain 95% confidence intervals for centroids based on Gower similarity between some mulivariate samples (community data from sediment cores). I have so far used the ...
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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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Hierarchical clustering with mixed type data - what distance/similarity to use?
In my dataset we have both continuous and naturally discrete variables. I want to know whether we can do hierarchical clustering using both type of variables. And if yes, what distance measure is ...
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