compute_centroids_c: Aggregate categorical data within clusters
In kbrulois/Dufy: A set of tools and algorithms for reducing the size of large datasets in a density-aware manner
compute_centroids_c R Documentation
Aggregate categorical data within clusters
Description
Aggregate categorical data within clusters
Usage
compute_centroids_c(data = dat, cluster = NULL, ambiguous_cutoff = 0.5)
Arguments
data
A numeric matrix of data where cells correspond to rows and genes correspond to columns
ambiguous_cutoff
Proportion of the most represented category in a cluster. Clusters falling below this cutoff will be considered ambiguous.
Value
A list that includes the following elements:
- cluster
A vector of length nrow(data) containing cluster assignments.
- d
A vector of length nrow(data) containing density values.
Author(s)
Kevin Brulois
kbrulois/Dufy documentation built on May 4, 2022, 3:54 a.m.
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| compute_centroids_c | R Documentation |
Aggregate categorical data within clusters
Description
Aggregate categorical data within clusters
Usage
compute_centroids_c(data = dat, cluster = NULL, ambiguous_cutoff = 0.5)
Arguments
data |
A numeric matrix of data where cells correspond to rows and genes correspond to columns |
ambiguous_cutoff |
Proportion of the most represented category in a cluster. Clusters falling below this cutoff will be considered ambiguous. |
Value
A list that includes the following elements:
- cluster
A
vectorof lengthnrow(data)containing cluster assignments.- d
A
vectorof lengthnrow(data)containing density values.
Author(s)
Kevin Brulois
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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