Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model.
Yi-Cheng HuangChing-Chen HouPublished in: Sensors (2023)
Keyphrases
- gaussian mixture model
- kullback leibler divergence
- probability density function
- feature engineering
- principal component analysis
- probability density
- mixture model
- feature space
- dependency parsing
- text classification
- information theoretic
- expectation maximization
- gaussian mixture
- mutual information
- density estimation
- feature vectors
- em algorithm
- distance measure
- generalized gaussian
- information theory
- machine learning
- maximum likelihood
- natural language processing
- gaussian distribution
- labeled data
- covariance matrix
- low dimensional
- speaker identification
- density function
- multiscale
- bayesian framework
- model selection
- dimensionality reduction
- probabilistic model
- hidden markov models
- marginal distributions
- bayesian networks
- feature extraction