The idea is to provide a standard interface
to users who use both R and Python for building machine learning models.
This package provides a scikit-learn's fit, predict interface to
train machine learning models in R.

Build Machine Learning Models Like Using Python's Scikit-Learn
Library in R

package-ubuntu-20.04-r-4.0.5#cran#superml-0.5.3

Computes the dot product between two given vectors.

<table summary="R argblock">
<tr valign="top">
<td><code>a</code></td>
<td>
numeric vector
</td>
</tr>
<tr valign="top">
<td><code>b</code></td>
<td>
numeric vector
</td>
</tr>
<tr valign="top">
<td><code>norm</code></td>
<td>
logical, compute normalised dot product, default=True
</td>
</tr>
</table>

numeric vector containing sdot product score

a <- runif(5)
b <- runif(5)
s <- dot(a, b)

package-ubuntu-20.04-r-4.0.5#cran#superml-0.5.3#docs#dot

dot

Description

Usage

Arguments

Value

Examples

superml

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`a`	numeric vector
`b`	numeric vector
`norm`	logical, compute normalised dot product, default=True