Search Results for author:
Found 9 papers, 0 papers with code
Causal Inference for Banking Finance and Insurance A Survey
This paper presents a comprehensive survey of 37 papers published during 1992-2023 and concerning the application of causal inference to banking, finance, and insurance.
FedPNN: One-shot Federated Classification via Evolving Clustering Method and Probabilistic Neural Network hybrid
Protecting data privacy is paramount in the fields such as finance, banking, and healthcare.
ATM Fraud Detection using Streaming Data Analytics
In both contexts, RF turned out to be the best model.
Chaotic Variational Auto encoder-based Adversarial Machine Learning
In this paper, we performed VAE-based adversary sample generation and applied it to various problems related to finance and cybersecurity domain-related problems such as loan default, credit card fraud, and churn modelling, etc., We performed both Evasion and Data-Poison attacks on Logistic Regression (LR) and Decision Tree (DT) models.
Chaotic Variational Auto Encoder based One Class Classifier for Insurance Fraud Detection
The effectiveness of C-VAE is demonstrated on the health insurance fraud and auto insurance datasets.
Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection
Owing to the rarity of fraudulent activities, Fraud detection can be formulated as either a binary classification problem or One class classification (OCC).
Parallel and Streaming Wavelet Neural Networks for Classification and Regression under Apache Spark
After the advent of big data, as data gets generated at a brisk pace, it is imperative to analyze it as soon as it is generated owing to the fact that the nature of the data may change dramatically in short time intervals.
Feature subset selection for Big Data via Chaotic Binary Differential Evolution under Apache Spark
Hence, we embed Logistic and Tent chaotic maps into the BDE and named it as Chaotic Binary Differential Evolution (CBDE).
Scalable Feature Subset Selection for Big Data using Parallel Hybrid Evolutionary Algorithm based Wrapper in Apache Spark
Owing to the emergence of large datasets, applying current sequential wrapper-based feature subset selection (FSS) algorithms increases the complexity.
