House price prediction using Artificial Neural Network (ANN) with adagrad optimizer
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The real estate market is a dynamic and complex ecosystem influenced by a myriad of
factors, making accurate price predictions a formidable challenge. Understanding the
intricate relationships between variables such as location, property characteristics, economic
indicators, and market trends is essential for making informed investment decisions, in this
thesis, a comprehensive exploration of machine learning and artificial neural networks
(ANNs) has been undertaken, laying the groundwork for understanding how these powerful
computational tools can be harnessed to solve complex problems across various domains.
The study began by delving into the fundamentals of machine learning, categorizing it into
its primary types, and discussing its applications in clustering, dimensionality reduction, and
learning association rules. These sections highlighted the versatility and breadth of machine
learning techniques in uncovering patterns and simplifying the complexities inherent in vast
datasets. Further, a transition was made into a focused discussion on linear regression,
including its simplest form and the more sophisticated gradient boosting method. This
progression underscored the evolution of machine learning from basic predictive modelling
to more advanced, iterative improvement techniques capable of handling nonlinear
relationships with exceptional accuracy and efficiency.
Açıklama
Anahtar Kelimeler
ANN, AdaGrad, Housing Price Prediction, ML, AI
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Abdulwahid, E. S. (2024). House price prediction using Artificial Neural Network (ANN) with adagrad optimizer. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
