Feature selection for online streaming high-dimensional data: A state-of-the-art review
Abstract Knowledge discovery for data streaming requires online feature selection to reduce
the complexity of real-world datasets and significantly improve the learning process. This is …
the complexity of real-world datasets and significantly improve the learning process. This is …
A review on imbalanced data classification techniques
Most all datasets that hold real-time data have an imbalanced organization of class
instances. The total quantity of instances in certain classes is substantially greater than other …
instances. The total quantity of instances in certain classes is substantially greater than other …
Perbandingan Evaluasi Kernel SVM untuk Klasifikasi Sentimen dalam Analisis Kenaikan Harga BBM: Comparative Evaluation of SVM Kernels for Sentiment …
S Rabbani, D Safitri, N Rahmadhani… - … : Indonesian Journal of …, 2023 - journal.irpi.or.id
Abstract Kebijakan perubahan harga Bahan Bakar Minyak (BBM) oleh pemerintah pada
September 2022 lalu menimbulkan kontroversi pengguna sosial media termasuk Twitter …
September 2022 lalu menimbulkan kontroversi pengguna sosial media termasuk Twitter …
Impact of SMOTE on imbalanced text features for toxic comments classification using RVVC model
Social media platforms and microblogging websites have gained accelerated popularity
during the past few years. These platforms are used for expressing views and opinions …
during the past few years. These platforms are used for expressing views and opinions …
An efficient CNN model for COVID‐19 disease detection based on x‐ray image classification
Artificial intelligence (AI) techniques in general and convolutional neural networks (CNNs) in
particular have attained successful results in medical image analysis and classification. A …
particular have attained successful results in medical image analysis and classification. A …
A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research
The combination of class imbalance and overlap is currently one of the most challenging
issues in machine learning. While seminal work focused on establishing class overlap as a …
issues in machine learning. While seminal work focused on establishing class overlap as a …
[HTML][HTML] Adaptive K-means clustering based under-sampling methods to solve the class imbalance problem
In the field of machine learning, the issue of class imbalance is a common problem. It refers
to an imbalance in the quantity of data collected, where one class has a significantly larger …
to an imbalance in the quantity of data collected, where one class has a significantly larger …
Improving classification performance in credit card fraud detection by using new data augmentation
E Strelcenia, S Prakoonwit - AI, 2023 - mdpi.com
In many industrialized and develo** nations, credit cards are one of the most widely used
methods of payment for online transactions. Credit card invention has streamlined …
methods of payment for online transactions. Credit card invention has streamlined …
An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry
Mobile communication has become a dominant medium of communication over the past two
decades. New technologies and competitors are emerging rapidly and churn prediction has …
decades. New technologies and competitors are emerging rapidly and churn prediction has …
[HTML][HTML] Classification of movie reviews using term frequency-inverse document frequency and optimized machine learning algorithms
Abstract The Internet Movie Database (IMDb), being one of the popular online databases for
movies and personalities, provides a wide range of movie reviews from millions of users …
movies and personalities, provides a wide range of movie reviews from millions of users …