ToolboxPerformance: Difference between revisions

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| 2015a || 8.1.1 || OS X El Capitan || 2.8 GHz Intel, 16 GB ram || cell || cell
| 2015a || 8.1.1 || OS X El Capitan || 2.8 GHz Intel, 16 GB ram || cell || cell
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'''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"
| |'''Test sample selection scheme'''
||
[[Image:Cv_vet.jpg||| ]]
|| 
[[Image:Cv_con.jpg||| ]]
|| 
[[Image:Cv_rnd.jpg||| ]]
|| 
[[Image:Cv_loo.jpg||| ]]
||
* User-defined subsets
* Can "force" specific objects into every test set, every model set, or exclude them from the CV procedure
|- valign="top"
| |'''Parameters'''
||
* Number of Data Splits (s)
* Maximum number of PCs/LVs
* Total number of objects/samples (n)
||
* Number of Data Splits (s)
* Maximum number of PCs/LVs
* Total number of objects/samples (n)
||
* Number of Data Splits (s)
* Number of iterations (r)
* Maximum number of PCs/LVs
* Total number of objects/samples (n)
||
* Maximum number of PCs/LVs
* Total number of objects/samples (n)
||
* Number of data splits (s)
* Object membership for each split
* All user-defined
* Total number of objects/samples (n)
|- valign="top"
| |'''Number of sub-validation experiments'''
||
= s
||
= s
||
= (s * r)
||
= n
||
= s
|-
|'''Number of test samples per sub-validation'''
||
= n/s
||
= n/s
||
= n/s
||
=1
||
* Can vary, user defined
|-
|}
|}

Revision as of 12:35, 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. Properties of different cross-validation methods in Solo and PLS_Toolbox.

Venetian Blinds Contiguous Blocks Random Subsets Leave-One Out Custom
Test sample selection scheme

Cv vet.jpg

Cv con.jpg

Cv rnd.jpg

Cv loo.jpg

  • User-defined subsets
  • Can "force" specific objects into every test set, every model set, or exclude them from the CV procedure
Parameters
  • Number of Data Splits (s)
  • Maximum number of PCs/LVs
  • Total number of objects/samples (n)
  • Number of Data Splits (s)
  • Maximum number of PCs/LVs
  • Total number of objects/samples (n)
  • Number of Data Splits (s)
  • Number of iterations (r)
  • Maximum number of PCs/LVs
  • Total number of objects/samples (n)
  • Maximum number of PCs/LVs
  • Total number of objects/samples (n)
  • Number of data splits (s)
  • Object membership for each split
  • All user-defined
  • Total number of objects/samples (n)
Number of sub-validation experiments

= s

= s

= (s * r)

= n

= s

Number of test samples per sub-validation

= n/s

= n/s

= n/s

=1

  • Can vary, user defined