On the chance accuracies of large collections of classifiers.
Mark PalatucciAndrew CarlsonPublished in: ICML (2008)
Keyphrases
- decision trees
- document collections
- support vector
- training data
- linear classifiers
- supervised classification
- feature set
- ensemble learning
- information retrieval
- feature selection
- metadata
- digital libraries
- svm classifier
- machine learning algorithms
- neural network
- classification rate
- training samples
- image classification
- data sets
- decision boundary
- machine learning approaches
- classifier ensemble
- majority voting
- multiple classifiers
- extracted features
- class labels
- test set
- support vector machine svm
- knn
- feature vectors
- training set
- machine learning