How Good is 85%?: A Survey Tool to Connect Classifier Evaluation to Acceptability of Accuracy.
Matthew KayShwetak N. PatelJulie A. KientzPublished in: CHI (2015)
Keyphrases
- individual classifiers
- high accuracy
- confusion matrix
- fold cross validation
- computational cost
- assessment tool
- classification accuracy
- support vector machine classifier
- classification rate
- classifier systems
- training data
- high classification accuracy
- roc curve
- evaluation method
- class labels
- accuracy rate
- precision and recall
- classification method
- classification algorithm
- training set
- highest accuracy
- improve the recognition accuracy
- leave one out cross validation
- unseen data
- multiple classifier systems
- significantly improves the accuracy
- data sets
- classifier combination
- learning classifier systems
- evaluation model
- linear classifiers
- error rate
- training samples
- support vector machine
- computational complexity
- decision trees
- feature selection
- machine learning