wls: Implement local linear regression with a Gaussian kernel, as...
In tbonza/supml: "Algorithms for Supervised Machine Learning"
Description
Usage
Arguments
Value
Description
Analytic solution using Strang 5th ed.
Usage
1
Arguments
y
target vector
w
weight vector
X
feature matrix without intercept column
Value
coefficients theta
tbonza/supml documentation built on May 17, 2019, 3:14 a.m.
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Description Usage Arguments Value
Description
Analytic solution using Strang 5th ed.
Usage
1 |
Arguments
y |
target vector |
w |
weight vector |
X |
feature matrix without intercept column |
Value
coefficients theta
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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