par10

This function reads a CSV file containing a matrix of values and modifies it as follows:
If a value in the matrix is 0, it is replaced by 10 times the maximum non-zero value in the corresponding row.

Implements the Bi-objective Lexicographical Classification method and Performance Assessment Ratio at 10% metric for algorithm classification. Constructs matrices representing algorithm performance under multiple criteria, facilitating decision-making in algorithm selection and evaluation. Analyzes and compares algorithm performance based on various metrics to identify the most suitable algorithms for specific tasks. This package includes methods for algorithm classification and evaluation, with examples provided in the documentation. Carvalho (2019) presents a statistical evaluation of algorithmic computational experimentation with infeasible solutions <doi:10.48550/arXiv.1902.00101>. Moreira and Carvalho (2023) analyze power in preprocessing methodologies for datasets with missing values <doi:10.1080/03610918.2023.2234683>.

Iago Augusto de Carvalho 

ppRank

Classification of Algorithms

Tiago Costa Soares 

par10 function

<dl><dt>G_file</dt>
<dd>The path to the CSV file containing the matrix of values.</dd>
<dt>has_header</dt>
<dd>Logical, indicating if the CSV file has a header row. Default is FALSE.</dd></dl>

Arguments

par10 Function — par10

<dl>

<dt>G_file</dt>
<dd>The path to the CSV file containing the matrix of values.</dd>


<dt>has_header</dt>
<dd>Logical, indicating if the CSV file has a header row. Default is FALSE.</dd>

</dl>

par10: par10 Function

Description

Usage

Value

Arguments

Examples