get_voronoi_feature_PART_dataset

<code>get_voronoi_feature_PART_dataset()</code> function returns
the feature (mapping) representation in RKHS based on Voronoi diagram for NEW PART of dataset.
The <code>Matrix_Voronoi</code> is based on the PREVIOUS dataset.
The NEW PART of dataset will appear at the end of PREVIOUS dataset

internal

Incorporates Approximate Bayesian Computation to get a posterior distribution and to select a model optimal parameter for an observation point. Additionally, the meta-sampling heuristic algorithm is realized for parameter estimation, which requires no model runs and is dimension-independent. A sampling scheme is also presented that allows model runs and uses the meta-sampling for point generation. A predictor is realized as the meta-sampling for the model output. All the algorithms leverage a machine learning method utilizing the maxima weighted Isolation Kernel approach, or 'MaxWiK'. The method involves transforming raw data to a Hilbert space (mapping) and measuring the similarity between simulated points and the maxima weighted Isolation Kernel mapping corresponding to the observation point. Comprehensive details of the methodology can be found in the papers Iurii Nagornov (2024) <doi:10.1007/978-3-031-66431-1_16> and Iurii Nagornov (2023) <doi:10.1007/978-3-031-29168-5_18>.

Yuri Nagornov

MaxWiK

Machine Learning Method Based on Isolation Kernel Mean Embedding

get_voronoi_feature_PART_dataset function

<dl><dt>data</dt>
<dd>Data.frame of new points</dd>
<dt>talkative</dt>
<dd>Logical parameter to print or do not print messages</dd>
<dt>start_row</dt>
<dd>Row number from which a new data should be added</dd>
<dt>Matrix_Voronoi</dt>
<dd>Matrix of Voronoi diagrams based on the PREVIOUS dataset</dd></dl>

Arguments

The function to get feature representation in RKHS based on Voronoi diagram for PART of dataset — get_voronoi_feature_PART_dataset

<dl>

<dt>data</dt>
<dd>Data.frame of new points</dd>


<dt>talkative</dt>
<dd>Logical parameter to print or do not print messages</dd>


<dt>start_row</dt>
<dd>Row number from which a new data should be added</dd>


<dt>Matrix_Voronoi</dt>
<dd>Matrix of Voronoi diagrams based on the PREVIOUS dataset</dd>

</dl>

get_voronoi_feature_PART_dataset: The function to get feature representation in RKHS based on Voronoi diagram for PART of dataset

Description

Usage

Value

Arguments

Examples