ToolboxPerformance: Difference between revisions

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'''Table 2. Performance of nnon-linear methods'''
 
 
 
 
''PCR'''


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| ||'''Venetian Blinds'''||'''Contiguous Blocks'''||'''Random Subsets'''||'''Leave-One Out'''||'''Custom'''
| ||'''100 variables'''||'''500 variables'''||'''1000 variables'''


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| |'''Test sample selection scheme'''
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'''Table 1. PLS'''
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| |'''100 samples'''
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'''Table 3. ANN'''
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'''Table 3. ANN'''
'''Table 4. SVM'''


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'''Table 4. SVM memory performance.'''


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'''Table 4. SVM'''
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'''SVM with PCA compression''


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Revision as of 13:40, 8 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



Table 1. PCA

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples






PCR'

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples




Table 1. PLS

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples






Table 3. ANN

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples





Table 4. SVM

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples



Table 4. SVM memory performance.

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples


'SVM with PCA compression

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples



Table 4. SVM memory performance.

100 variables 500 variables 1000 variables
100 samples


500 samples


1000 samples