A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees.
Parisa GolbayaniIonut FlorescuRupak ChatterjeePublished in: CoRR (2020)
Keyphrases
- decision trees
- neural network
- support vector
- learning machines
- large margin classifiers
- logistic regression
- credit scoring
- support vector regression
- pattern recognition
- training algorithm
- collaborative filtering
- fuzzy decision trees
- naive bayes
- cross validation
- radial basis function
- prediction model
- back propagation
- classification accuracy
- fuzzy logic
- multi class
- artificial neural networks
- predictive model
- decision tree induction
- machine learning
- backpropagation neural networks
- short term
- feature selection
- user preferences
- decision rules
- maximum margin
- loss function
- multilayer perceptron
- support vector machine
- nearest neighbour
- training set
- hyperplane
- knowledge management
- neural network model
- learning algorithm
- svm classifier
- decision tree learning
- forecasting model
- case study
- training data
- risk analysis
- exchange rate
- machine learning algorithms
- kernel function
- multi layer perceptron
- recurrent neural networks
- feature space
- classification rules
- knn
- kernel methods
- generalization ability
- random forest
- credit risk
- neural nets
- soft margin
- training examples
- genetic algorithm