Comparación del nivel de precisión de los clasificadores Support Vector Machines, k Nearest Neighbors, Random Forests, Extra Trees y Gradient Boosting en el reconocimiento de actividades infantiles utilizando sonido ambiental.
Diego M. Blanco-MurilloAntonio García-DomínguezCarlos Eric Galván-TejadaJosé M. Celaya-PadillaPublished in: Res. Comput. Sci. (2018)
Keyphrases
- random forests
- k nearest neighbor
- gradient boosting
- loss function
- support vector
- logistic regression
- decision trees
- base learners
- knn
- support vector machine
- learning machines
- nearest neighbor
- ensemble methods
- del gobierno
- random forest
- feature selection
- machine learning algorithms
- generalization ability
- text categorization
- kernel function
- ensemble learning
- support vector machine svm
- classification algorithm
- input space
- pairwise
- cross validation
- svm classifier
- naive bayes
- machine learning
- kernel methods
- training set
- hyperplane
- classification accuracy
- prediction accuracy
- radial basis function
- distance function
- data sets
- multi class
- learning tasks
- relational databases
- regression problems
- training data
- data mining
- neural network