Black Fungus Classification using Adaboost with SVM-based classifier and Compare accuracy with Support Vector Machine.
Panthangi Venkata Sai CharanG. RamkumarPublished in: IC3I (2022)
Keyphrases
- support vector machine
- support vector
- svm classifier
- multi class
- fold cross validation
- high classification accuracy
- support vector machine svm
- generalization ability
- classification accuracy
- feature selection
- classification method
- training data
- svm classification
- classification algorithm
- recursive feature elimination
- unseen data
- decision boundary
- feature space
- support vector machine classifier
- ensemble classifier
- binary classifiers
- individual classifiers
- feature vectors
- feature reduction
- machine learning
- classification rate
- binary classification
- ensemble learning
- binary classification problems
- kernel function
- small sample
- hyperplane
- majority voting
- soft margin
- decision stumps
- k nearest neighbour
- k nearest neighbor
- adaboost algorithm
- highest accuracy
- training set
- classification scheme
- classification process
- training process
- decision trees
- multiclass classification
- multi class classification
- knn
- higher classification accuracy
- classifier ensemble
- binary decision tree
- receiver operating characteristic curves
- object detection
- feature set
- multiple classifier systems
- class labels
- weak learners
- cost sensitive
- text classification
- image classification
- training samples
- face detection
- train a support vector machine
- base classifiers