Machine learning algorithms for smart data analysis in internet of things environment: taxonomies and research trends
Machine learning techniques will contribution towards making Internet of Things (IoT)
symmetric applications among the most significant sources of new data in the future. In this …
symmetric applications among the most significant sources of new data in the future. In this …
Cyberbullying severity detection: A machine learning approach
BA Talpur, D O'Sullivan - PloS one, 2020 - journals.plos.org
With widespread usage of online social networks and its popularity, social networking
platforms have given us incalculable opportunities than ever before, and its benefits are …
platforms have given us incalculable opportunities than ever before, and its benefits are …
Kernelized support vector machine with deep learning: an efficient approach for extreme multiclass dataset
M Zareapoor, P Shamsolmoali, DK Jain, H Wang… - Pattern Recognition …, 2018 - Elsevier
Classification with thousands of classes and a large number of features is often
computationally intractable. The presence of irrelevant features can decrease the …
computationally intractable. The presence of irrelevant features can decrease the …
Data-dependent generalization bounds for multi-class classification
In this paper, we study data-dependent generalization error bounds that exhibit a mild
dependency on the number of classes, making them suitable for multi-class learning with a …
dependency on the number of classes, making them suitable for multi-class learning with a …
Automatic feature scaling and selection for support vector machine classification with functional data
A Jiménez-Cordero, S Maldonado - Applied Intelligence, 2021 - Springer
FunctionalData Analysis (FDA) has become a very important field in recent years due to its
wide range of applications. However, there are several real-life applications in which hybrid …
wide range of applications. However, there are several real-life applications in which hybrid …
Machine learning techniques for IoT data analytics
Tremendous advancements and innovations in hardware and software together with
developments in different communication technologies and computational advancements …
developments in different communication technologies and computational advancements …
A scalable algorithm for multi-class support vector machine on geo-distributed datasets
Training machine learning models on large scale data to efficiently discover valuable
information while maintaining the security and privacy of data remains an important research …
information while maintaining the security and privacy of data remains an important research …
Enhancement of Scalability of SVM Classifiers for Big Data
V Bhajantri, SG Totad… - Advances in Data …, 2023 - Wiley Online Library
With todays' modern technology and lifestyle, vast amounts of data are generated
exponentially day by day. Storing, processing, and analyzing such huge data is a complex …
exponentially day by day. Storing, processing, and analyzing such huge data is a complex …
[PDF][PDF] Generalization error bounds for extreme multi-class classification
Extreme multi-class classification is multi-class learning using an extremely large number of
label classes. We show generalization error bounds with a mild dependency (up to …
label classes. We show generalization error bounds with a mild dependency (up to …
[PDF][PDF] PREDICTING CYBER BULLYING ON SOCIAL MEDIA IN THE BIG DATA ERA USING EXTREME LEARNING MACHINE
VC Sekhar, CS Sri - ijarst.in
Cyber bullying disturbs harassment online, with alarming implications. It exists in different
ways, and is in textual format in most social networks. There is no question that over 1.96 …
ways, and is in textual format in most social networks. There is no question that over 1.96 …