Hyperparameters tuning of random forest with harmony search in credit scoring
Correct identification of defaulters and non-defaulters in the lending industry is a crucial task for financial institutions. Credit scoring is a tool utilized for credit granting decisions. Recently, Random Forest (RF) is actively researched in credit scoring due to two main benefits, i.e. non-para...
Saved in:
Main Authors: | Goh, Rui Ying, Lee, Lai Soon, Adam, Mohd. Bakri |
---|---|
Format: | Article |
Language: | English |
Published: |
Academy of Sciences Malaysia
2019
|
Online Access: | http://psasir.upm.edu.my/id/eprint/80123/1/Hyperparameters%20tuning%20of%20random%20forest%20with%20harmony%20search%20in%20credit%20scoring.pdf http://psasir.upm.edu.my/id/eprint/80123/ https://www.akademisains.gov.my/asmsj/article/hyperparameters-tuning-of-random-forest-with-harmony-search-in-credit-scoring/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hybrid harmony search-artificial intelligence models in credit scoring
by: Goh, Rui Ying
Published: (2019) -
Credit scoring: a review on support vector machines and metaheuristic approaches
by: Goh, Rui Ying, et al.
Published: (2019) -
Hyperparameter tuning of the model for hunger state classification
by: Razman, Mohd Azraan, et al.
Published: (2020) -
Hyperparameter tuning and pipeline optimization via grid search method and tree-based AutoML in breast cancer prediction
by: Mat Radzi, Siti Fairuz, et al.
Published: (2021) -
Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment
by: Ahmed Hamza, Manar, et al.
Published: (2022)