Multi-class Recognition of Alzheimer's and Parkinson's diseases using Bag of Deep reduced Features (BoDrF) with Improved Chaotic Multi Verse Harris Hawks Optimization (CMVHHO) and Random Forest (RF) based classification for early diagnosis.
Chetan BalajiD. S. SureshPublished in: Comput. methods Biomech. Biomed. Eng. Imaging Vis. (2023)
Keyphrases
- multi class
- random forest
- feature set
- early diagnosis
- feature extraction
- feature selection
- support vector machine
- base classifiers
- multiclass classification
- multi class classification
- classification accuracy
- binary classifiers
- feature vectors
- decision trees
- fold cross validation
- skin lesion
- cost sensitive
- random forests
- svm classifier
- feature space
- class labels
- computer aided diagnosis
- extracted features
- svm classification
- ensemble classifier
- pattern recognition
- classification models
- computer aided
- support vector
- feature subset
- high dimensionality
- machine learning
- early detection
- cardiovascular disease
- classification algorithm
- support vector machine svm
- pairwise
- binary classification
- object recognition
- text classification
- ensemble methods
- data sets
- benchmark datasets
- model selection
- supervised learning
- instance selection
- knowledge discovery
- infectious disease
- training set
- data mining