Machine Learning Classifier Approach with Gaussian Process, Ensemble boosted Trees, SVM, and Linear Regression for 5G Signal Coverage Mapping.
Akansha GuptaKamal Kumar GhanshalaRamesh C. JoshiPublished in: Int. J. Interact. Multim. Artif. Intell. (2021)
Keyphrases
- gaussian process
- linear regression
- machine learning
- regression problems
- decision trees
- support vector machine
- support vector
- feature selection
- random forests
- hyperparameters
- training data
- model selection
- gaussian processes
- training set
- svm classifier
- least squares
- ensemble learning
- ensemble methods
- learning algorithm
- latent variables
- random forest
- bayesian framework
- regression model
- support vector machine svm
- semi supervised
- cross validation
- learning machines
- machine learning algorithms
- feature space
- generalization ability
- kernel function
- decision boundary
- classification accuracy
- kernel methods
- base classifiers
- machine learning methods
- supervised learning
- multi class
- active learning
- knn
- non stationary
- logistic regression
- learning tasks
- feature vectors
- binary classification
- classification trees
- labeled data
- random sampling
- text categorization
- naive bayes
- ls svm
- class labels
- text mining
- support vector regression
- prior knowledge
- pairwise
- feature extraction