gradientDescentCpp: gradient descnet method
In WilsonImmunologyLab/LinQView: Integrate information from both transcriptome and cell surface protein signals to better identify cell heterogeneity
Description
gradient descnet method
Usage
1
gradientDescentCpp(X, Y, alpha, learning_rate, low_threshold, max_iter)
Arguments
X
distance vector.
Y
distance vector.
alpha
initial value of parameter alpha.
learning_rate
learning rate of GD method
low_threshold
the low threshold of GD
max_iter
maximum iterations
WilsonImmunologyLab/LinQView documentation built on Jan. 3, 2022, 10 p.m.
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Description
gradient descnet method
Usage
1 | gradientDescentCpp(X, Y, alpha, learning_rate, low_threshold, max_iter)
|
Arguments
X |
distance vector. |
Y |
distance vector. |
alpha |
initial value of parameter alpha. |
learning_rate |
learning rate of GD method |
low_threshold |
the low threshold of GD |
max_iter |
maximum iterations |
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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