kme.default

kme.mild_df

Function to calculate the kernel mean embedding for to distributional data
sets. It uses the empirical approximation for the integral
$$\int_{\mathcal X} \int_{\mathcal Y} K(x, y) d P_X d Q_Y $$ for a given
kernel $K(\cdot, \cdot)$. Currently only supports radial basis function
kernel for fast computation.

Weakly supervised (WS), multiple instance (MI) data lives in
numerous interesting applications such as drug discovery, object
detection, and tumor prediction on whole slide images. The 'mildsvm'
package provides an easy way to learn from this data by training
Support Vector Machine (SVM)-based classifiers. It also contains
helpful functions for building and printing multiple instance data
frames. The core methods from 'mildsvm' come from the following
references: Kent and Yu (2024) <doi:10.1214/24-AOAS1876>; Xiao, Liu, and Hao
(2018) <doi:10.1109/TNNLS.2017.2766164>; Muandet et al. (2012)
<https://proceedings.neurips.cc/paper/2012/file/9bf31c7ff062936a96d3c8bd1f8f2ff3-Paper.pdf>;
Chu and Keerthi (2007) <doi:10.1162/neco.2007.19.3.792>; and Andrews
et al. (2003)
<https://papers.nips.cc/paper/2232-support-vector-machines-for-multiple-instance-learning.pdf>.
Many functions use the 'Gurobi' optimization back-end to improve the
optimization problem speed; the 'gurobi' R package and associated
software can be downloaded from <https://www.gurobi.com> after
obtaining a license.

Sean Kent

mildsvm

Multiple-Instance Learning with Support Vector Machines

Yifei Liou

kme function

<dl><dt>df</dt>
<dd>A data.frame of <code>mild_df</code> object, must have column
<code>'instance_name'</code> which defines the instances.</dd>
<dt>df2</dt>
<dd>A data.frame, <code>mild_df</code> object, or <code>NULL</code> (default <code>NULL</code>).</dd>
<dt>sigma</dt>
<dd>The parameter for <code>'radial'</code> kernel (default <code>0.05</code>).</dd>
<dt>...</dt>
<dd>Additional arguments passed to methods.</dd></dl>

Arguments

<ul>
<li><code>kme(default)</code>: Default S3 method</li>
<li><code>kme(mild_df)</code>: S3 method for class <code>mild_df</code></li>
</ul>

Methods (by class)

Author

Calculate the kernel mean embedding matrix — kme

<dl>

<dt>df</dt>
<dd>A data.frame of <code>mild_df</code> object, must have column
<code>'instance_name'</code> which defines the instances.</dd>


<dt>df2</dt>
<dd>A data.frame, <code>mild_df</code> object, or <code>NULL</code> (default <code>NULL</code>).</dd>


<dt>sigma</dt>
<dd>The parameter for <code>'radial'</code> kernel (default <code>0.05</code>).</dd>


<dt>...</dt>
<dd>Additional arguments passed to methods.</dd>

</dl>

kme: Calculate the kernel mean embedding matrix

Description

Usage

Value

Arguments

Methods (by class)

Author

Details

Examples