meu_mv_impr: meu_mv_impr: Part of DCEM package.
In parichit/DCEM: Clustering Big Data using Expectation Maximization Star (EM*) Algorithm
Description
Usage
Arguments
Value
Description
Initialize the meu(s) by randomly selecting the samples from the dataset. It uses the proposed
implementation from K-means++: The Advantages of Careful Seeding, David Arthur and Sergei
Vassilvitskii. URL http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf.
Usage
1
2
# Randomly seeding the meu.
meu_mv_impr(data, num_meu)
Arguments
data
(matrix): The dataset provided by the user.
num_meu
(numeric): The number of meu.
Value
A matrix containing the selected samples from the dataset.
parichit/DCEM documentation built on Jan. 22, 2022, 6:13 p.m.
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Description Usage Arguments Value
Description
Initialize the meu(s) by randomly selecting the samples from the dataset. It uses the proposed implementation from K-means++: The Advantages of Careful Seeding, David Arthur and Sergei Vassilvitskii. URL http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf.
Usage
1 2 | # Randomly seeding the meu.
meu_mv_impr(data, num_meu)
|
Arguments
data |
(matrix): The dataset provided by the user. |
num_meu |
(numeric): The number of meu. |
Value
A matrix containing the selected samples from the dataset.
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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