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principal component analysis (59) 59
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Journal of Medical Imaging and Health Informatics, ISSN 2156-7018, 02/2016, Volume 6, Issue 1, pp. 194 - 203
Journal Article
Journal Article
Neural Processing Letters, ISSN 1370-4621, 2009, Volume 30, Issue 2, pp. 113 - 132
The Mixture of Probabilistic Principal Components Analyzers (MPPCA) is a multivariate analysis technique which defines a Gaussian probabilistic model at each... 
Dimensionality reduction | Missing value imputation | Probability density estimation | Probabilistic principal components analysis (PPCA) | Cross-validation | Simulated annealing | MIXTURES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Journal Article
Applied Mechanics and Materials, ISSN 1660-9336, 04/2014, Volume 536-537, Issue Advances in Mechatronics, Robotics and Automation II, pp. 26 - 29
A new method for bearing fault diagnosis is proposed based on Probabilistic Principal Component Analysis (PPCA) and Cyclic Bispectrum (CB). The first procedure... 
Fault diagnosis | Cyclic bispectrum | PPCA | Rolling bearings | Faults | Computer simulation | Roller bearings | Probability theory | Mathematical models | Bearing
Journal Article
Korean Journal of Chemical Engineering, ISSN 0256-1115, 8/2017, Volume 34, Issue 8, pp. 2135 - 2146
Journal Article
Journal Article
Chemical Engineering Science, ISSN 0009-2509, 09/2014, Volume 116, pp. 296 - 305
Journal Article
Journal Article
2014 7th International Conference on Intelligent Computation Technology and Automation, 10/2014, pp. 312 - 317
The missing data problem exists in a lot of transportation systems while many traffic applications require accurate traffic data to work well. So, various... 
Accuracy | Automation | Detectors | Data Imputation | Temporal and Spatial Information | Probabilistic logic | MPPCA | Spatial databases | Probability distribution | PPCA | Principal component analysis
Conference Proceeding
Journal of Computational and Graphical Statistics, ISSN 1061-8600, 01/2015, Volume 24, Issue 1, pp. 66 - 83
To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful.... 
Classification and clustering | Algorithms | Multivariate analysis | Exploratory data analysis | Graphical methods | Mixture models | MODELS | STATISTICS & PROBABILITY | VARIABLES | CLUSTER-ANALYSIS
Journal Article
Journal of Statistical Planning and Inference, ISSN 0378-3758, 05/2020, Volume 206, pp. 249 - 262
Principal component analysis (PCA) is widely used in various fields to reduce high dimensional data sets to lower dimensions. Traditionally, the first a few... 
Sufficient dimension reduction | Envelope model | Grassmann manifolds | Principal components | NUMBER | DIMENSION REDUCTION | COMPONENTS | STATISTICS & PROBABILITY | ALGORITHMS
Journal Article