Improving Risk Predictions by Preprocessing Imbalanced Credit Data

Imbalanced credit data sets refer to databases in which the class of defaulters is heavily under-represented in comparison to the class of non-defaulters. This is a very common situation in real-life credit scoring applications, but it has still received little attention. This paper investigates whether data resampling can be used to improve the performance of learners built from imbalanced credit data sets, and whether the effectiveness of resampling is related to the type of classifier. Experimental results demonstrate that learning with the resampled sets consistently outperforms the use of the original imbalanced credit data, independently of the classifier used

Computational modelling of microcrack interaction and its effect on the life of a ceramic tool

Journal of Materials Processing Tech.232223-231JMPT

Non-invasive fecal metabonomic detection of colorectal cancer

10.4161/cbt.27625Cancer Biology and Therapy154389-39

Investigating the role of nucleoside transporters in the resistance of colorectal cancer to 5-fluorouracil therapy

10.1007/s00280-012-2054-0Cancer Chemotherapy and Pharmacology713817-823CCPH

Investigation of the drug-drug interaction between α-lipoic acid and valproate via mitochondrial β-oxidation

10.1007/s11095-008-9681-5Pharmaceutical Research25112639-2649PHRE

New mosquito species records (Diptera: Culicidae) from Singapore

Nine species of mosquitoes in eight genera are recorded for the first time in Singapore. An additional two species were overlooked in a 1986 checklist for mosquitoes in Singapore, and one was described after 1986. Location and habitat data are provided for the nine new records. With the inclusion of these new records the number of species reported from Singapore is 137

Safety and efficacy of human rotavirus vaccine during the first 2 years of life in Asian infants: Randomised, double-blind, controlled study

10.1016/j.vaccine.2009.07.098Vaccine27435936-594