ToolboxPerformance: Difference between revisions
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==PLS_Toolbox Performance== | ==PLS_Toolbox Performance== | ||
This page presents performance results from the main regression methods in PLS_Toolbox to allow comparison of their time and memory requirements when analyzing datasets of various sizes. These results were obtained using a Mac OSX (El Capitan) computer with a 2.8 GHz Intel CPU and 16 GB RAM. Matlab version R2015a and PLS_Toolbox version 8.1 were used. | |||
All results were obtained by building models from the command line using synthetic random datasets. Autoscale preprocessing was used with the default option values for all methods. Cross-validation was not performed. | |||
All results were obtained by building models from the command line | |||
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| |'''20000 samples''' | | |'''20000 samples''' | ||
|| .2 GB | || 0.2 GB | ||
|| 1 | || 1 GB | ||
|| 4 GB | || 4 GB | ||
|- valign="top" | |- valign="top" | ||
| |'''50000 samples''' | | |'''50000 samples''' | ||
|| .5 GB | || 0.5 GB | ||
|| 4 GB | || 4 GB | ||
|| 11 | || 11 | ||
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| |'''50000 samples''' | | |'''50000 samples''' | ||
|| .6 GB | || 0.6 GB | ||
|| 3 GB | || 3 GB | ||
|| 6.75 GB | || 6.75 GB | ||
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|| 550 | || 550 | ||
|| 2810 | || 2810 | ||
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Latest revision as of 21:35, 13 September 2016
PLS_Toolbox Performance
This page presents performance results from the main regression methods in PLS_Toolbox to allow comparison of their time and memory requirements when analyzing datasets of various sizes. These results were obtained using a Mac OSX (El Capitan) computer with a 2.8 GHz Intel CPU and 16 GB RAM. Matlab version R2015a and PLS_Toolbox version 8.1 were used.
All results were obtained by building models from the command line using synthetic random datasets. Autoscale preprocessing was used with the default option values for all methods. Cross-validation was not performed.
PCA time in seconds required to build 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 | 0.2 GB | 1 GB | 3.5 GB |
50000 samples | 3.55 | 9 GB | 10.5 GB |
PCR time in seconds required to build 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 | 0.2 GB | 1 GB | 4 GB |
50000 samples | 0.5 GB | 4 GB | 11 |
PLS time in seconds required to build 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 build 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 | 3.5 GB |
50000 samples | 0.6 GB | 3 GB | 6.75 GB |
ANN time in seconds required to build model
100 variables | 500 variables | 1000 variables | |
500 samples | 6 | 28 | 95 |
1000 samples | 10 | 370 | 360 |
2000 samples | 12 | 550 | 2810 |
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 build 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 |