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Development and Optimization of a Multi-Label SVM for Chemogenomics

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10243313" target="_blank" >RIV/61989100:27740/19:10243313 - isvavai.cz</a>

  • Result on the web

    <a href="https://zenodo.org/record/2809567" target="_blank" >https://zenodo.org/record/2809567</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Development and Optimization of a Multi-Label SVM for Chemogenomics

  • Original language description

    Support vector machine (SVM) based machine learning is used in a wide range of domains. It represents a family of supervised machine learning algorithms and is most commonly used for binary classification tasks. It can also be extended to multi-label problems which are specializations of multi-task classification. We use an early stage SVM implementation, called PermonSVM, to implement a one versus all multi-label method to classify and predict protein-compound activities in chemogenomics. The white paper highlights the VI-HPS tools Score-P, Cube and Vampir, as used during the early development and improvement processes of PermonSVM. We apply those tools to identify and analyze a bottleneck in the early PermonSVM implementation, and verify its final iteration.

  • Czech name

  • Czech description

Classification

  • Type

    V<sub>souhrn</sub> - Summary research report

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Number of pages

    12

  • Place of publication

  • Publisher/client name

    PRACE - Partnership for Advanced Computing in Europe.

  • Version