Konu "Machine Learning" için listeleme
Toplam kayıt 15, listelenen: 1-15
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Antimicrobial peptide activity prediction using machine learning methods
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional antibiotics in order to overcome the growing problems of antibiotic resistance. Computational prediction approaches receive an increasing ... -
Comparison of Machine Learning Classifiers for Protein Secondary Structure Prediction
(IEEE, 2018)Proteinlerin üç boyutlu yapılarının tahmin edilmesi teorik kimya ve biyoenformatik için önemli problemlerden biridir. Protein yapı tahmininin en önemli aşamalarından biri ise ikincil yapı tahminidir. Protein veritabanlarındaki ... -
Credit Card Fraud Detection with Machine Learning Methods
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 01.01.2019)With the increase in credit card usage of people, the credit card transactions increase dramatically. It is difficult to identify fraudulent transactions among the vast amount of credit card transactions. Although credit ... -
Data Mining Techniques in Direct Marketing on Imbalanced Data using Tomek Link Combined with Random Under-sampling
(Association for Computing Machinery, 2021)Determining the potential customers is very important in direct marketing. Data mining techniques are one of the most important methods for companies to determine potential customers. However, since the number of potential ... -
DEVELOPING A LABEL PROPAGATION APPROACH FOR CANCER SUBTYPE IDENTIFICATION PROBLEM
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2021)Kanser terimi, anormal hücrelerin kontrolden çıkıp diğer dokuları istila ettiği hastalıkları tanımlamak için kullanılır. Çok sayıda kanser türü vardır ve birçok kanser türü, farklı klinik ve biyolojik etkileri olan çeşitli ... -
Developing machine learning methods for business intelligence
(Abdullah Gül Üniversitesi, 2018)Detection of key attributes in text is an area of research, which attracts attention due to the increase of data and the availability of massive documents. Key attributes serve as metadata for documents and the discovery ... -
Developing machine learning methods for network anomaly detection
(Abdullah Gül Üniversitesi, 2018)Machine learning refers to training of a computer (machine) to be able to acquire knowledge from data (i.e. experience) and improve itself on a given task. The field of machine learning has become a mainstream, improving ... -
DEVELOPMENT OF DATA MINING METHODOLOGIES AND MACHINE LEARNING MODELS TO UNDERSTAND CARDIOVASCULAR DISEASE MECHANISMS
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2020)World Health Organization (WHO) reported that in 2016, 31% (17.9 million) of the total deaths in the world were caused by Coronary Artery Disease (CAD) and it is estimated that around 23.6 million people will die from ... -
Ensemble Churn Prediction for Internet Service Provider with Machine Learning Techniques
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2020)With the developing technology in every fields, a competitive marketing environment has been arised In this competitive environment analyzing customer behavior has become vital In particular, the ability to easily change ... -
An Ensemble Feature Selection Methodology That Incorporates Domain Knowledge for Cardiovascular Disease Diagnosis
(IEEE, 2020)Koroner Arter Hastalığı (KAH), arterlerin duvarlarında aterom denilen yağlı madde birikiminin bir sonucu olarak kalbin yeterince beslenememesi durumudur. KAH, 2016 yılında dünyadaki toplam ölümlerin %31'ine (17,9 milyon) ... -
A Hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS) Approach for Professional Bloggers Classification
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019)Despite their small numbers, some users of the online social networks demonstrate the ability to influence others. Bloggers are one of such kind of users that through their ideas and opinions on different topics, influence ... -
Image processing based analysis and quantification of micro biomaterials and cells for biochip
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)Quantification of tumor cells is essential for early cancer detection and progression tracking. Multiple techniques have been devised to detect tumor cells. In addition to conventional laboratory instruments, several ... -
MACHINE LEARNING BASED INTEGRATION OF miRNA AND mRNA PROFILES COMBINED WITH FEATURE GROUPING AND RANKING
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2021)It is very important to understand the development and progression mechanisms of the diseases at the molecular level. Revealing the functional mechanisms that cause the disease not only contributes to the molecular ... -
A review of on-device machine learning for IoT: An energy perspective
(ELSEVIER, 2024)Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image classification, human activity recognition, ... -
YSA KULLANILARAK MAMOGRAMLARDAN DOKUSAL ÖZNİTELİK TABANLI MEME KANSERİ İLGİ BÖLGESİ SINIFLANDIRILMASI
(TÜBİTAK ULAKBİM Ulusal Akademik Ağ ve Bilgi Merkezi Cahit Arf Bilgi Merkezi, 2020)Radyoloji uzmanlarının mamografi görüntülerine bakarak yaptığı meme kanseri teşhislerinde tip bir hata oranı yüzde otuzlara kadar çıkmaktadır. Kanserin teşhis başarısını artırmak adına bu çalışmada uzmanlara yardımcı olacak ...