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ITS » Master Theses » Statistika - S2 Posted by tondoindra@gmail.com at 20/04/2016 15:44:56 • 1868 Views
RARE EVENT WEIGHTED LOGISTIC REGRESSION
FOR CLASSIFICATION OF IMBALANCED DATA
Case Study The Classification of Underdeveloped Rural
In East Java Province
Author : SULASIH, DIAN EKA APRIANA ( 1314201714 )
ABSTRAK
Salah satu permasalahan dalam klasifikasi data adalah komposisi data yang tidak
seimbang imbalanced data. Pada klasifikasi imbalanced data classifier
cenderung memprediksi kelas yang memiliki komposisi data lebih besar sehingga
didapatkan akurasi prediksi yang baik terhadap kelas data training yang banyak
kelas mayoritas dan akurasi prediksi yang buruk untuk kelas data training yang
sedikit kelas minoritas. Oleh karena itu diperlukan metode yang tepat untuk
melakukan klasifikasi pada imbalanced data. Rare Event Weighted Logistic
Regression RE-WLR adalah metode klasifikasi imbalanced data untuk data
berukuran besar dan rare event. RE-WLR dikembangkan dari Truncated
Regularized Iteratively Re-weighted Least Square TR-IRLS dengan rare event
correction pada Regresi Logistik. Penelitian ini bertujuan untuk mengkaji dan
menerapkan RE-WLR untuk klasifikasi imbalanced data dengan studi kasus
klasifikasi desa tertinggal di Provinsi Jawa Timur tahun 2014 serta untuk
membandingkan tingkat ketepatan klasifikasi antara metode RE-WLR dan TRIRLS
pada kasus tersebut. Hasil penelitian menunjukkan bahwa secara deskriptif
RE-WLR memberikan kinerja klasifikasi yang lebih baik dibandingkan TR-IRLS
namun dengan perbedaan yang tidak signifikan. Rata-rata nilai sensitifity RE-WLR
juga lebih tinggi daripada TR-IRLS. Hal ini menunjukkan bahwa RE-WLR bisa
memprediksi kelas minoritas rare event atau desa tertinggal dengan lebih baik
dibandingkan TR-IRLS.
ABSTRACT
One of the problems in data classification is the composition of the data that is out
of balance imbalanced data. In the classification of imbalanced data most of the
classifier are biased towards the major class and have very poor classification
rates on minor class. Rare Event Weighted Logistic Regression RE-WLR is a
method of classification applied to large imbalanced data and rare event. REWLR
is developed from Truncated Regularized Iteratively Re-weighted Least
Squares TR-IRLS with rare event correction to Logistic Regression. This study
aims to assess and apply the RE-WLR to the classification of imbalanced data
with study case classification of underdeveloped rural in East Java Province in
2014 and to compare the accuracy between RE-WLR method and TR-IRLS in
that case. The results shows that RE-WLR provides better classification
performance than TR-IRLS but the difference is not significant. The average
value of RE-WLRs sensitifity is also higher than TR-IRLS. This shows that the
RE-WLR could predict the minority class rare event or underdeveloped rural
better than TR-IRLS.
Keywords:
Desa Tertinggal, Imbalanced Data, Klasifikasi ,RE-WLR, TR-IRLS
Subject
: Analisis Regresi
Contributor
Santi Wulan Purnami, M.Si., Ph.D.
Santi Puteri Rahayu, M.Si., Ph.D.
Date Create
: 20/04/2016
Type
: Text
Format
: PDF
Language
: Indonesian
Identifier
: ITS-Master-13103150001613
Collection ID
: 13103150001613
Call Number
: RTSt 519.536 Sul r
Source Master Theses Of Statistics RTSt 519.536 Sul r, 2016
Coverage ITS Community
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