Search Results - subject:"undersampling"

Predicting the length of stay in hospital emergency rooms in Rhode Island

Lamere, Alicia T.; Nguyen, Son; Niu, Gao; Olinsky, Alan; … - In: Advances in business and management forecasting 14 (2021), pp. 35-48

Persistent link: https://www.econbiz.de/10014291661

Effects of resampling techniques on imbalanced data classification : a new under-resampling method

Nguyen, Son; Schumacher, Phyllis; Olinsky, Alan; Quinn, John - In: Advances in business and management forecasting 14 (2021), pp. 51-70

Persistent link: https://www.econbiz.de/10014291699

Data imbalance in autism pre-diagnosis classification systems : an experimental study

Abdelhamid, Neda; Padmavathy, Arun; Peebles, David; … - In: Journal of information & knowledge management : JIKM 19 (2020) 1, pp. 2040014-1-2040014-16

Persistent link: https://www.econbiz.de/10012292628

Detecting non-injured passengers and drivers in car accidents : a new under-resampling method for imbalanced classification

Nguyen, Son; Niu, Gao; Quinn, John T.; Olinsky, Alan; … - In: Advances in business and management forecasting 13 (2019), pp. 93-105

Persistent link: https://www.econbiz.de/10012154907

Sampling method based on improved C4.5 decision tree and its application in prediction of telecom customer churn

Deng, Weibin; Deng, Linsen; Liu, Jin; Qi, Jie - In: International journal of information technology and … 18 (2019) 1, pp. 93-109

Persistent link: https://www.econbiz.de/10012056968

Predictive Modeling for Imbalanced Big Data in SAS Enterprise Miner and R

Nguyen, Son; Olinsky, Alan; Quinn, John; Schumacher, Phyllis - In: International Journal of Fog Computing (IJFC) 1 (2018) 2, pp. 83-108

of the rare events, undersampling of the common events in the data, and synthetic minority over-sampling technique (SMOTE …

Persistent link: https://www.econbiz.de/10012044789

Detection of Automobile Insurance Fraud Using Feature Selection and Data Mining Techniques

Subudhi, Sharmila; Panigrahi, Suvasini - In: International Journal of Rough Sets and Data Analysis … 5 (2018) 3, pp. 1-20

is subjected to the Possibilistic Fuzzy C-Means (PFCM) clustering technique for the undersampling approach. The 10-fold …

Persistent link: https://www.econbiz.de/10012047413

On the relative importance of the hot stove effect and the tendency to rely on small samples

Fujikawa, Takemi - In: Judgment and Decision Making 4 (2009) 5, pp. 429-435

Experiments have suggested that decisions from \textit{experience} differ from decisions from \textit{description}. In experience-based decisions, the decision makers often fail to maximise their payoffs. Previous authors have ascribed the effect of underweighting of rare outcomes to this...

Persistent link: https://www.econbiz.de/10005108384

Handling class imbalance in customer churn prediction

BUREZ, J.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2008

), we investigated the increase in performance of sampling (both random and advanced under-sampling) and two specific … practice (Ling and Li, 1998). Results show that under-sampling can lead to improved prediction accuracy, especially when …

Persistent link: https://www.econbiz.de/10004983021

Undersampling power-law size distributions: effect on the assessment of extreme natural hazards

Geist, Eric; Parsons, Tom - In: Natural Hazards 72 (2014) 2, pp. 565-595

The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests …

Persistent link: https://www.econbiz.de/10010846399