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...
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 |
Similar Items
-
Hybrid Harmony Search–Artificial Intelligence Models in Credit Scoring
by: Rui Ying Goh, et al.
Published: (2020-09-01) -
Hybrid harmony search-artificial intelligence models in credit scoring
by: Goh, Rui Ying
Published: (2019) -
Hyperparameter Tuning on Classification Algorithm with Grid Search
by: Wahyu Nugraha, et al.
Published: (2022-05-01) -
Optimal hyperparameter tuning of random forests for estimating causal treatment effects
by: Lateef Amusa, et al.
Published: (2021-08-01) -
Agent-Based Collaborative Random Search for Hyperparameter Tuning and Global Function Optimization
by: Ahmad Esmaeili, et al.
Published: (2023-05-01)