Do We Need to Observe Features to Perform Feature Selection?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F18%3A00323850" target="_blank" >RIV/68407700:21240/18:00323850 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Do We Need to Observe Features to Perform Feature Selection?
Original language description
Many feature selection methods were developed in the past, but in the core, they all work the same way — you pass a set of features to the algorithm and get a reduced set of the features. But can we perform a non-trivial feature selection without first observing the features? This is an important question because if we were actually able to predict feature importance before observing the features, we would reduce computation requirements of all stages of machine learning process beginning with feature engineering. In this article, we argue that it is possible to predict feature importance before feature vector observation. The trick is that we use meta-features about the features to perform the feature selection. We evaluate the concept on 15 relational databases. On average, it was enough to generate the top decile of all features to get the same model accuracy as if we generated all features and passed them to the model.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA18-18080S" target="_blank" >GA18-18080S: Fusion-Based Knowledge Discovery in Human Activity Data</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 18th Conference Information Technologies - Applications and Theory (ITAT 2018)
ISBN
9781727267198
ISSN
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e-ISSN
1613-0073
Number of pages
8
Pages from-to
44-51
Publisher name
CEUR Workshop Proceedings
Place of publication
Aachen
Event location
Krompachy
Event date
Sep 21, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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