Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal
Multiple classifier application to credit risk assessment
Fifty Years of Classification and Regression Trees 1
consumer credit - risk models via machine - learning algorithms q .
Example-dependent cost-sensitive decision trees
The Research and Analysis in Decision Tree Algorithm Based on C4.5 Algorithm
Comprehensible Credit Scoring Models Using Rule Extraction From Support Vector Machines
Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications
Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research
A Proposed Classification of Data Mining Techniques in Credit Scoring
On-line Random Forests
Using semi-supervised classifiers for credit scoring (Accepted for Publication)
Prediction analysis of risky credit using Data mining classification models
Machine Learning on imbalanced data in Credit Risk
Learning Decision Trees for Unbalanced Data
Exploratory Data Analysis using Random Forests ∗
A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification
Checkpoint Ensembles: Ensemble Methods from a Single Training Process
Stacking Bagged and Boosted Forests for Effective Automated Classification
Comparison of Performance of Decision Tree Algorithms and Random Forest: An Application on OECD Countries Health Expenditures
BDT: Gradient Boosted Decision Tables for High Accuracy and Scoring Efficiency
Design of Substrate Integrated Waveguide Components
Friending, IMing, and Hanging Out Face-to-Face: Overlap in Adolescents' Online and Offline Social Networks
An enhanced neural network technique for software risk analysis
Real-time dynamic wrinkling of coarse animated cloth
Multi-scale pyramid pooling for deep convolutional representation