model is used to build classification model trained with space vectors based on machine learning algorithms (which is described in Section 4.4).
Parallel mining algorithm including parallel association rules algorithm, parallel classification
algorithm and parallel clustering algorithm for massive data classification or prediction model, data summary, data clustering, association rules, sequential patterns, dependency relationship or dependence model, and found abnormal trend etc..
method has been proposed to archive a faster remote sensing images training speed [6,7].
Last but not least, the optimization over parallel classification technique was also investigated.
Plus, due to the advance of parallelism, novel face recognition architecture was proposed by applying parallelism for large matrix manipulation including parallel preprocessing, parallel recognition, and parallel classification, all of which refer to Parallel Expectation-Maximization PCA or PEM-PCA.
There exist some parallel classification
and clustering algorithms.
The reliability was tested through parallel classifications. These data were collected separately during two-week periods in the same departments.
In all, 144 parallel classifications were obtained.
The parallel classifications, independently performed by two nurses, indicated satisfactory interrater reliability.