Feature Engineering

Alp Ustundag; Mahmut Sami Sivri; Kenan Menguc

doi:10.1007/978-3-030-93823-9_6

Feature Engineering

Alp Ustundag^*, Mahmut Sami Sivri, Kenan Menguc

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Bölüm › bilirkişi

5 Atıf (Scopus)

Özet

As the amount of data generated and collected grows, analyzing and modeling so many input variables get more difficult. So, it is important to reduce model complexity and establish simple, accurate and robust models. Feature engineering is the process of using domain knowledge to extract input variables from raw data, prioritize them and select the best ones so that machine learning algorithms work well and model performance is improved.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Springer Series in Advanced Manufacturing
Yayınlayan	Springer Nature
Sayfalar	153-169
Sayfa sayısı	17
DOI'lar	https://doi.org/10.1007/978-3-030-93823-9_6
Yayın durumu	Yayınlandı - 2022

Yayın serisi

Adı	Springer Series in Advanced Manufacturing
ISSN (Basılı)	1860-5168
ISSN (Elektronik)	2196-1735

Bibliyografik not

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Belgeye Erişim

10.1007/978-3-030-93823-9_6

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Feature Engineering",

abstract = "As the amount of data generated and collected grows, analyzing and modeling so many input variables get more difficult. So, it is important to reduce model complexity and establish simple, accurate and robust models. Feature engineering is the process of using domain knowledge to extract input variables from raw data, prioritize them and select the best ones so that machine learning algorithms work well and model performance is improved.",

author = "Alp Ustundag and Sivri, {Mahmut Sami} and Kenan Menguc",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

year = "2022",

doi = "10.1007/978-3-030-93823-9_6",

language = "English",

series = "Springer Series in Advanced Manufacturing",

publisher = "Springer Nature",

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booktitle = "Springer Series in Advanced Manufacturing",

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TY - CHAP

T1 - Feature Engineering

AU - Ustundag, Alp

AU - Sivri, Mahmut Sami

AU - Menguc, Kenan

PY - 2022

Y1 - 2022

N2 - As the amount of data generated and collected grows, analyzing and modeling so many input variables get more difficult. So, it is important to reduce model complexity and establish simple, accurate and robust models. Feature engineering is the process of using domain knowledge to extract input variables from raw data, prioritize them and select the best ones so that machine learning algorithms work well and model performance is improved.

AB - As the amount of data generated and collected grows, analyzing and modeling so many input variables get more difficult. So, it is important to reduce model complexity and establish simple, accurate and robust models. Feature engineering is the process of using domain knowledge to extract input variables from raw data, prioritize them and select the best ones so that machine learning algorithms work well and model performance is improved.

UR - http://www.scopus.com/inward/record.url?scp=85151494534&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-93823-9_6

DO - 10.1007/978-3-030-93823-9_6

M3 - Chapter

AN - SCOPUS:85151494534

T3 - Springer Series in Advanced Manufacturing

SP - 153

EP - 169

BT - Springer Series in Advanced Manufacturing

PB - Springer Nature

ER -

Feature Engineering

Özet

Yayın serisi

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap