Increasing the accuracy of neural network classification using refined training data.
Taskin KavzogluPublished in: Environ. Model. Softw. (2009)
Keyphrases
- classification accuracy
- training data
- neural network
- training process
- training set
- decision trees
- pattern recognition
- learning vector quantization
- training patterns
- accuracy rate
- classification models
- classification rate
- supervised learning
- support vector machine
- predictive accuracy
- classification method
- test data
- high accuracy
- image classification
- training samples
- class labels
- support vector
- feature selection
- unseen data
- learning algorithm
- naive bayes
- annotation effort
- feature space
- data sets
- pattern classification
- kohonen self organizing map
- classification algorithm
- machine learning
- support vector machine svm
- active learning
- fold cross validation
- multi layer perceptron
- computational cost
- roc curve
- text classification
- generalization ability
- machine learning algorithms
- prediction accuracy
- error rate
- test set
- nearest neighbour
- prior knowledge
- probabilistic neural network
- feature vectors
- random selection
- artificial neural networks
- labeled instances
- feature extraction
- back propagation