The rapid growth in e-commerce has resulted in an increasing number of people shop**
online. These shoppers depend on credit cards as a payment method or use mobile wallets …

This paper proposes a method, called autoencoder with probabilistic random forest (AE-
PRF), for detecting credit card frauds. The proposed AE-PRF method first utilizes the …

This paper proposes a method called autoencoder with probabilistic LightGBM (AED-LGB)
for detecting credit card frauds. This deep learning-based AED-LGB algorithm first extracts …

In an increasingly digitalized commerce landscape, the proliferation of credit card fraud and
the evolution of sophisticated fraudulent techniques have led to substantial financial losses …

The conventional feature selection methods fail to work on imbalanced datasets due to the
overfitting issue caused by the extremely imbalanced positive and negative samples. In …

Expeditious growth in e-commerce has emerged in an increasing number of online
shop** societies. These shoppers rely on credit cards as a payment method or use a …

Perkembangan kejahatan transaksi fraud kartu kredit memberikan dampak kerugian
finansial bagi pemegang kartu. Pengembangan model deteksi transaksi fraud …

Common binary classification algorithms which learn directly from imbalanced data can lead
to a bias towards the majority class. Although the over-sampling technology can solve the …

As a result of rapid digitisation, online transactions using credit cards have become popular.
With this, fraudulent activities have also increased considerably. Although many supervised …

Предмет исследования. Несбалансированность классов в наборах данных негативно
влияет на системы машинной классификации, применяемые в таких приложениях …