Simplicity is Best: Addressing the Computational Cost of Machine Learning Classifiers in Constrained Edge Devices.
Oihane Gómez-CarmonaDiego Casado-MansillaDiego López-de-IpiñaJavier García-ZubíaPublished in: IOT (2019)
Keyphrases
- machine learning
- computational cost
- machine learning algorithms
- machine learning methods
- machine learning approaches
- decision trees
- feature selection
- supervised classification
- edge detection
- training data
- naive bayes
- meta learning
- computer vision
- computational effort
- pattern recognition
- training set
- mobile devices
- learning problems
- edge information
- learning tasks
- test set
- learning algorithm
- weighted graph
- reduce the computational cost
- support vector
- roc analysis
- natural language processing
- multiple classifiers
- statistical methods
- support vector machine
- computational complexity
- training samples
- multiple classifier systems
- explanation based learning
- classification systems
- linear classifiers
- data mining
- inductive learning
- active learning
- classification method
- classification algorithm
- svm classifier
- training examples
- ensemble learning
- mobile applications
- smart phones
- multiscale
- image processing
- artificial intelligence
- information extraction
- learning classifier systems
- ensemble classifier
- neural network