ToolboxPerformance: Difference between revisions
Jump to navigation
Jump to search
imported>Mathias |
imported>Mathias |
||
Line 16: | Line 16: | ||
'''Table 1. Properties of different cross-validation methods in Solo and PLS_Toolbox.''' | '''Table 1. Properties of different cross-validation methods in Solo and PLS_Toolbox.''' | ||
{| border="1" cellpadding="5" cellspacing="0" | |||
| ||'''Venetian Blinds'''||'''Contiguous Blocks'''||'''Random Subsets'''||'''Leave-One Out'''||'''Custom''' | |||
|- valign="top" | |||
| | | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- valign="top" | |||
| | | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- valign="top" | |||
| | | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- | |||
| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- | |||
|} | |||
'''Table 2. Performance of nnon-linear methods''' | |||
{| border="1" cellpadding="5" cellspacing="0" | {| border="1" cellpadding="5" cellspacing="0" | ||
Line 24: | Line 95: | ||
| |'''Test sample selection scheme''' | | |'''Test sample selection scheme''' | ||
|| | || | ||
|| | || | ||
|| | || | ||
|| | || | ||
|| | || | ||
|- valign="top" | |||
| |'''100 Samples'' | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- valign="top" | |||
| |'''500 Samples''' | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- | |||
|'''1000 samples''' | |||
|| | |||
|| | |||
|| | |||
|| | |||
|| | |||
|- | |||
|} | |||
'''Table 2. Performance of nnon-linear methods''' | |||
{| border="1" cellpadding="5" cellspacing="0" | |||
| ||'''Venetian Blinds'''||'''Contiguous Blocks'''||'''Random Subsets''' | |||
|- valign="top" | |||
| |'''Test sample selection scheme''' | |||
|| | |||
|| | |||
|| | |||
|- valign="top" | |- valign="top" | ||
| |'''Parameters''' | | |'''Parameters''' | ||
|| | || | ||
|| | || | ||
|| | || | ||
|- valign="top" | |||
| |'''Number of sub-validation experiments''' | |||
|| | || | ||
|| | || | ||
|| | |||
|- | |||
|} | |||
'''Table 3. ANN''' | |||
{| border="1" cellpadding="5" cellspacing="0" | |||
| ||'''Venetian Blinds'''||'''Contiguous Blocks'''||'''Random Subsets''' | |||
|- valign="top" | |- valign="top" | ||
| |''' | | |'''Test sample selection scheme''' | ||
|| | |||
|| | |||
|| | |||
|- valign="top" | |||
| |'''Parameters''' | |||
|| | |||
|| | || | ||
|| | || | ||
= | |||
|- valign="top" | |||
| |'''Number of sub-validation experiments''' | |||
|| | || | ||
|| | || | ||
|| | || | ||
|- | |- | ||
|''' | |||
|} | |||
'''Table 4. SVM''' | |||
{| border="1" cellpadding="5" cellspacing="0" | |||
| ||'''100 variables'''||'''500 variables'''||'''1000 variables''' | |||
|- valign="top" | |||
| |'''100 samples''' | |||
|| | |||
|| | |||
|| | |||
|- valign="top" | |||
| |'''500 samples''' | |||
|| | |||
|| | || | ||
|| | || | ||
= | |||
|- valign="top" | |||
| |'''1000 samples''' | |||
|| | || | ||
|| | || | ||
|| | || | ||
|- | |- | ||
|} | |} |
Revision as of 13:22, 8 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 |
Table 1. Properties of different cross-validation methods in Solo and PLS_Toolbox.
Venetian Blinds | Contiguous Blocks | Random Subsets | Leave-One Out | Custom | |
| |||||
|
| ||||
|
Table 2. Performance of nnon-linear methods
Venetian Blinds | Contiguous Blocks | Random Subsets | Leave-One Out | Custom | |
Test sample selection scheme |
| ||||
'100 Samples | |||||
500 Samples |
|
| |||
1000 samples |
|
Table 2. Performance of nnon-linear methods
Venetian Blinds | Contiguous Blocks | Random Subsets | |
Test sample selection scheme |
| ||
Parameters |
| ||
Number of sub-validation experiments |
|
Table 3. ANN
Venetian Blinds | Contiguous Blocks | Random Subsets | |
Test sample selection scheme |
| ||
Parameters |
| ||
Number of sub-validation experiments |
|
Table 4. SVM
100 variables | 500 variables | 1000 variables | |
100 samples |
| ||
500 samples |
| ||
1000 samples |
|