ToolboxPerformance: Difference between revisions
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Revision as of 11:07, 13 September 2016
PLS_Toolbox Performance
The following performance results are for general comparison and expectation. Your own mileage may vary.
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 |
|