ToolboxPerformance: Difference between revisions

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'''Table 1. PCA'''
'''PCA time in seconds required to train model'''


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'''PCR'''
'''PCR time in seconds required to train model'''


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''' PLS'''
''' PLS time in seconds required to train model'''


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'''LWR'''
'''LWR time in seconds required to train model'''


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'''Table 3. ANN'''
'''ANN time in seconds required to train model'''


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'''Table 4. SVM'''
'''SVM time in seconds required to train model'''


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'''SVM with PCA compression'''
'''SVM with PCA compression time in seconds required to train model'''


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Revision as of 11:04, 13 September 2016

PLS_Toolbox Performance

The following performance results are for general comparison and expectation. Your own mileage may vary.


Performance Table
Matlab Versoin PLS_Toolbox Version Operating System System Description Data Description Algorithm Performance Result
2015a 8.1.1 OS X El Capitan 2.8 GHz Intel, 16 GB ram cell cell



PCA time in seconds required to train model

1000 variables 2000 variables 5000 variables
20000 samples 2 4.7 40


50000 samples 3.5 9 61



PCA memory requirements

1000 variables 2000 variables 5000 variables
20000 samples .2 GB 1 GB 3.5 GB


50000 samples 3.55 9 GB 61 GB




PCR time in seconds required to train model

1000 variables 2000 variables 5000 variables
20000 samples 3 6 44


50000 samples 5 12 71



PCR memory requirements

1000 variables 2000 variables 5000 variables
20000 samples .2 GB 1 4 GB


50000 samples .5 GB 4 GB 11


PLS time in seconds required to train model

1000 variables 2000 variables 5000 variables
20000 samples 3.3 8 43


50000 samples 8 18 98



PLS Memory requirements

100 variables 500 variables 1000 variables
100 samples 1 GB 2 GB 5 GB


500 samples 1.6 GB 5.2 GB 13 GB





LWR time in seconds required to train model

1000 variables 5000 variables 10000 variables
20000 samples 4 65 76


50000 samples 10 77 670




LWR memory requirements

1000 variables 2000 variables 5000 variables
20000 samples <1 GB 2 GB 3.4 GB


50000 samples .6 GB 3 GB 6.75 GB




ANN time in seconds required to train model

100 variables 500 variables 1000 variables
500 samples 6 28 95


1000 samples 10 370 360


2000 samples 12 550 2810 s



SVM time in seconds required to train model

100 variables 500 variables 2000 variables
100 samples 8 28 105


500 samples 150 640 2370


1000 samples



SVM with PCA compression time in seconds required to train model

100 variables 500 variables 1000 variables
100 samples 4 4 4


500 samples 38 38 38


1000 samples


SVM memory requirements

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples