The Credit Card Datasets are taken for making decisions to grant/deny loans based on the details we extract from it. We propose an algorithm Called Particle Swarm Optimization Algorithm (PSO) to produce an optimized result for decision making process. New measures are used to measure the ...
因为异常一般指的相对不常见的现象,因此发生的机率必然要小很多。因此正常类的样本量会远远高于异常类的样本量,一般高达几个数量级。比如:疾病相关的样本,正常的样本会远高于疾病的样本,即便是当下流行的COVID-19。比如kaggle 竞赛的信用卡交易欺诈(credit card fraud),正常交易与欺诈类交易比例大于10000:1。再比如工...
The first example presents as data on whether individuals have defaulted on their mortgage, and interest lies in determining whether other information, such as an individuals credit card debt, can be used to predict whether they will default or not. The second example considers data on flights ...
Default of Credit Card Clients Credit default data for Taiwanese creditors. Various features about each account are given. 30,000 Text Classification 2016 [347][348] I. Yeh Weather[edit] Dataset Name Brief description Preprocessing Instances Format Default Task Created (updated) Reference Creator Clou...
Yeh, I. C., & Lien, C. H. (2009). The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert Systems with Applications, 36(2), 2473-2480. 1. 简介 此数据集包含有关2005年4月至2005年9月台湾地区信用卡客户的默认付款,人口...
(2015) used credit card data to reconstruct individual movements. Show abstract Mapping household direct energy consumption in the United Kingdom to provide a new perspective on energy justice 2016, Energy Research and Social Science Citation Excerpt : By interpolating between the test dates, it is...
Let’s say you call your bank, and you get put into the IVR Phone System –‘Please tell us the department you’re looking for, press 1 for accounts, press 2 for a credit card, Press 3 for payment.’ The problem is that customers calling into that IVR, say the same thing to get...
machine-learningcorrelationmachine-learning-algorithmspcaoutlier-detectionuci-datasetdefault-of-credit-card-clients UpdatedJun 7, 2021 Jupyter Notebook mahmutakyol/diabet-data-mining Star2 Code Issues Pull requests Early-stage diabetes risk prediction dataset simple UI example for data mining lesson ...
Semi-supervised Credit Card Fraud Detection via Attribute-driven Graph Representation 26 Jun 2023 157 Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection 19 Apr 2021 96 Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks 16 Apr 2021 69 RLC-GNN...
The data consists of a formatting of the EFH dataset, which creates delinquency variables at the household level for mortgage and consumer loans, loan motivations, and non-payment of banking or retail credit card debt. Household measures of permanent income and unemployment risk were included based...