Araştırma Makalesi

An Approach Towards the Least-Squares Method for Simple Linear Regression

Cilt: 2 Sayı: 2 23 Eylül 2022
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An Approach Towards the Least-Squares Method for Simple Linear Regression

Öz

This study approaches the least-squares method for simple linear regression model. The least-squares line does not comply with the data when there are outliers that have deceptive effects on the results in the dataset. The study aims to develop a method for obtaining a line that complies more with the data when there are outliers in the dataset.

Anahtar Kelimeler

Kaynakça

  1. Miller I, Miller M. Mathematical Statistics, Prenttice-Hall, Inc, 1999 (Çev. Ümit Şenesen John E. Freund’dan Matematiksel İstatistik, Literatür Yayıncılık. 2007).
  2. Arslan İ. Python ile Veri Bilimi, Pusula Yayıncılık, Türkiye, 2020.
  3. Rousseeuw PJ, Leroy AM. Robust regression and outlier detection. John Wiley & Sons, 1987.
  4. Attaway S. Matlab A Practical Introduction to Programming and Problem Solving. 5th ed. Cambridge, USA, Butterwoth-Heinmann, 2019.
  5. Kubat C. Matlab Yapay Zeka ve Mühendislik Uygulamaları. 5. Baskı, İstanbul, Türkiye, Abaküs Kitap Yayın, 2021.
  6. Güneş A, Yıldız K. Matlab Matematik ve Grafik Programlama Dili. İstanbul, Türkiye, Türkmen Kitabevi, 1997.
  7. Verardi V, Croux C. “Robust regression in Stata”. The Stata Journal, 9(3), 439-453, 2009.
  8. Andersen R. Modern methods for robust regression (No. 152). Sage, 2008.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapay Zeka, Matematik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

23 Eylül 2022

Gönderilme Tarihi

7 Aralık 2021

Kabul Tarihi

1 Temmuz 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 2 Sayı: 2

Kaynak Göster

APA
Tali, H. H., & Çelti, C. (2022). An Approach Towards the Least-Squares Method for Simple Linear Regression. Advances in Artificial Intelligence Research, 2(2), 38-44. https://doi.org/10.54569/aair.1032607
AMA
1.Tali HH, Çelti C. An Approach Towards the Least-Squares Method for Simple Linear Regression. Adv. Artif. Intell. Res. 2022;2(2):38-44. doi:10.54569/aair.1032607
Chicago
Tali, Hasan Halit, ve Ceren Çelti. 2022. “An Approach Towards the Least-Squares Method for Simple Linear Regression”. Advances in Artificial Intelligence Research 2 (2): 38-44. https://doi.org/10.54569/aair.1032607.
EndNote
Tali HH, Çelti C (01 Eylül 2022) An Approach Towards the Least-Squares Method for Simple Linear Regression. Advances in Artificial Intelligence Research 2 2 38–44.
IEEE
[1]H. H. Tali ve C. Çelti, “An Approach Towards the Least-Squares Method for Simple Linear Regression”, Adv. Artif. Intell. Res., c. 2, sy 2, ss. 38–44, Eyl. 2022, doi: 10.54569/aair.1032607.
ISNAD
Tali, Hasan Halit - Çelti, Ceren. “An Approach Towards the Least-Squares Method for Simple Linear Regression”. Advances in Artificial Intelligence Research 2/2 (01 Eylül 2022): 38-44. https://doi.org/10.54569/aair.1032607.
JAMA
1.Tali HH, Çelti C. An Approach Towards the Least-Squares Method for Simple Linear Regression. Adv. Artif. Intell. Res. 2022;2:38–44.
MLA
Tali, Hasan Halit, ve Ceren Çelti. “An Approach Towards the Least-Squares Method for Simple Linear Regression”. Advances in Artificial Intelligence Research, c. 2, sy 2, Eylül 2022, ss. 38-44, doi:10.54569/aair.1032607.
Vancouver
1.Hasan Halit Tali, Ceren Çelti. An Approach Towards the Least-Squares Method for Simple Linear Regression. Adv. Artif. Intell. Res. 01 Eylül 2022;2(2):38-44. doi:10.54569/aair.1032607

Cited By

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