Survey of credit card anomaly and fraud detection using sampling techniques
The rapid growth in e-commerce has resulted in an increasing number of people shopping
online. These shoppers depend on credit cards as a payment method or use mobile wallets …
online. These shoppers depend on credit cards as a payment method or use mobile wallets …
A machine learning method for classification of cervical cancer
Cervical cancer is one of the leading causes of premature mortality among women
worldwide and more than 85% of these deaths are in developing countries. There are …
worldwide and more than 85% of these deaths are in developing countries. There are …
Toward privacy preservation using clustering based anonymization: recent advances and future research outlook
With the continuous increase in avenues of personal data generation, privacy protection has
become a hot research topic resulting in various proposed mechanisms to address this …
become a hot research topic resulting in various proposed mechanisms to address this …
Solving misclassification of the credit card imbalance problem using near miss
In ordinary credit card datasets, there are far fewer fraudulent transactions than ordinary
transactions. In dealing with the credit card imbalance problem, the ideal solution must have …
transactions. In dealing with the credit card imbalance problem, the ideal solution must have …
An ensemble-based approach for automated medical diagnosis of malaria using EfficientNet
G Marques, A Ferreras, I de la Torre-Diez - Multimedia tools and …, 2022 - Springer
Abstract Each year, more than 400,000 people die of malaria. Malaria is a mosquito-borne
transmissible infection that affects humans and other animals. According to World Health …
transmissible infection that affects humans and other animals. According to World Health …
The prediction of cardiac abnormality and enhancement in minority class accuracy from imbalanced ECG signals using modified deep neural network models
Cardiovascular disease (CVD) is the most fatal disease in the world, so its accurate and
automated detection in the early stages will certainly support the medical expert in timely …
automated detection in the early stages will certainly support the medical expert in timely …
Text mining and emotion classification on monkeypox Twitter dataset: A deep learning-natural language processing (NLP) approach
Emotion classification has become a valuable tool in analyzing text and emotions people
express in response to events or crises, particularly on social media and other online …
express in response to events or crises, particularly on social media and other online …
Parallel and incremental credit card fraud detection model to handle concept drift and data imbalance
A Somasundaram, S Reddy - Neural Computing and Applications, 2019 - Springer
Real-time fraud detection in credit card transactions is challenging due to the intrinsic
properties of transaction data, namely data imbalance, noise, borderline entities and …
properties of transaction data, namely data imbalance, noise, borderline entities and …
Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media
This paper presents a comprehensive evaluation of data pre-processing and word
embedding techniques in the context of Arabic document classification in the domain of …
embedding techniques in the context of Arabic document classification in the domain of …
A deep learning-based hyperspectral object classification approach via imbalanced training samples handling
Object classification in hyperspectral images involves accurately categorizing objects based
on their spectral characteristics. However, the high dimensionality of hyperspectral data and …
on their spectral characteristics. However, the high dimensionality of hyperspectral data and …