Machine-learning-based investigation on classifying binary and multiclass behavior outcomes of children with PIMD/SMID.
Von Ralph Dane Marquez HerbuelaTomonori KaritaYoshiya FurukawaYoshinori WadaYoshihiro YagiShuichiro SenbaEiko OnishiTatsuo SaekiPublished in: CoRR (2021)
Keyphrases
- multi class
- machine learning
- multiclass learning
- binary classifiers
- support vector machine
- error correcting output codes
- multi class svms
- multiclass classification
- feature selection
- binary classification
- multiclass problems
- cost sensitive
- multi class classification
- machine learning algorithms
- pairwise
- binary classification problems
- error correcting output coding
- multiple classes
- data mining
- machine learning methods
- decision trees
- constrained optimization
- multinomial logistic regression
- neural network
- active learning
- learning problems
- perceptron algorithm
- text classification
- multiclass support vector machines
- supervised learning
- text mining
- multi class problems
- model selection
- cost sensitive learning
- support vector machine svm
- cross validation
- kernel methods
- base classifiers