Sammon and Evri faq: Difference between pages

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===Purpose===
__TOC___
==Importing / Exporting==


Computes the Sammon projection of multivariate data to lower dimension.
[[faq_concatenate_multiple_files|How do I concatenate multiple files into a single DataSet?]]


===Synopsis===
[[faq_create_multivariate_image_from_separate_images|How do I create a multivariate image from separate images?]]


[[faq_export_PCA_scores_and_loadings_to_text_file|How do I export PCA scores and loadings to a text file (to read into MS Excel, for example)?]]


:p = sammon(x, ncolout, ''options'')
[[faq_import_three-way_data|How do I import three-way data into Solo or PLS_Toolbox?]]
:p = sammon(x, p, ''options'')


===Description===
[[faq_import_horiba_NGC_64bit |Why can't I import a Horiba NGC file on my 64-bit computer?]]


The Sammon algorithm maps points from a higher dimensional space to a lower dimensional space in such a way as to preserve the relative interpoint distances.
[[faq_SPCREADR_cant_read_multiple_files |Why can't SPCREADR read multiple files I've selected?]]


SAMMON is based on algorithm described in:
[[faq_some_EXCEL_files_fail_to_import |Why do some Excel files fail to import?]]
Sammon, JW (1969): A nonlinear mapping for data structure analysis, IEEE Transactions on Computers 18: 401–409.
Note that in the original paper, the term "y" is used for the projections. In this function, the projections are referred to as "p" to avoid confusion with regression functions.


====Inputs====
==General==
*'''x''' = (matrix or dataset) data to be projected.
*'''ncolout''' = number of output dimensions in the Sammon projection, OR
*'''p''' = the initial projection matrix, with size nrow by ncolout.


====Outputs====
[[faq_PARALIND_in_PLS_Toolbox |Can I do PARALIND in PLS_Toolbox?]]
* '''p''' = (matrix or dataset) projected coordinates of each data point. Dimension >= 2


===Options===
[[faq_install_on_more_than_one_PC | Can I install PLS_Toolbox (or Solo) on more than one PC, such as on my desktop and laptop computer?]]


options =  a structure array with one or more of the following fields:
[[faq_multiple_class_sets_together_in_SIMCA_PLSDA_LDA | Can I use multiple class sets (categorical variables) together in a SIMCA, PLSDA, or LDA model?]]


* '''niterations''': number of iterations performed.
[[faq_more_info_on_R_Squared_statistic | Can you give me more information on the R-Squared statistic?]]
* '''maxseconds''': Maximum number of seconds allowed. Overrides niterations.
* '''alpha''': [0.2] Sammon's "magic factor"
* '''D''': (matrix) Intersample Euclidean distance, size nrow x nrow.
* '''plots''': [ 'none' | {'final'} ] governs level of plotting.
* '''display''': [ 'on' | {'off'} ] governs level of display to command window.
* '''maxsamples''': [ 2000 ] Maximum number of samples for which Sammon projection will be calculated for. If an array or dataset has more than this number of samples, the Sammon projections will be returned as all NaN's. This is because the algorithm can be quite slow with many samples.


===Example===
[[faq_how_RMSEC_and_RMSECV_related to R2Y_and_Q2Y_seen_other_software | How are RMSEC and RMSECV related to R2Y and Q2Y I see in other software?]]


This example code shows the use of SAMMON on the 'arch' dataset, reducing the dimensionality from 10 to 2 while trying to preserving the interpoint spacing. The resulting plot shows the four classes:
[[faq_convergence_of_PARAFAC| Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings?]]
<pre>
load arch
opts.plots='final';
p = sammon(arch.data,2,opts)
</pre>
The resulting 75x2 array contains the Sammon projection of the 75x10 input array.


If the input data is a dataset with sample classes then the produced plot shows the projected points colored according to their class. Here we see five classes, the four 'arch' classes plus class 0, the unknowns.
[[faq_does_software_stop_working_if_maintenance_expires | Does the software stop working if my maintenance expires?]]
<pre>
load arch
opts.plots='final';
p = sammon(arch,2,opts)
colorbar
</pre>


===See Also===
[[faq_report_a_problem_with_PLS_Toolbox | How and where do I report a problem with PLS_Toolbox?]]


[[PCA]]
[[faq_how_are_T_contributions_calculated | How are T-contributions calculated?]]
 
[[faq_how_are_ROC_curves_calculated_for_PLSDA | How are the ROC curves calculated for PLSDA?]]
 
[[faq_how_are_error_bars_calculated_regression_model | How are the error bars calculated for a regression model and can they be related to a confidence limit (confidence in the prediction)?]]
 
[[faq_improve_performance_with_PLS_Toolbx_and_Matlab_on_Mac | How can I improve performance with PLS_Toolbox and Matlab on the Mac platform?]]
 
[[faq_assign_classes_for_samples_in_a_DataSet | How do I assign classes for samples in a DataSet?]]
 
[[faq_build_a_classification_model_from_class_set_other_than_the_first | How do I build a classification model from a class set other than the first?]]
 
[[faq_choose_between_different_cross_validation_leave_out_options | How do I choose between the different cross-validation leave-out options?]]
 
[[faq_reference_Eigenvector| How do I cite/reference Eigenvector?]]
 
[[faq_interpret_ROC_curves_and_Sensitivity_Specificity_plots_from_PLSDA | How do I interpret the ROC curves and Sensitivity / Specificity plots from PLSDA?]]
 
[[faq_make_DataSet_backwards_compatible | How do I make a DataSet backwards compatible?]]
 
[[faq_obtain_or_use_recompilation_license_for_PLS_Toolbox | How do I obtain or use a recompilation license for PLS_Toolbox?]]
 
[[faq_use_custon_cross_validation_option | How do I use the "custom" cross-validation option?]]
 
[[faq_out_of_memory_error_when_analyzing_data | I keep getting "out of memory" errors when analyzing my data. What can I do?]]
 
[[faq_java_lang_OutOfMemoryError| What can I do if I get a java.lang.OutOfMemoryError error?]]
 
[[faq_why_get_negative_scores_when_all_modes_are_set_to_nonnegativity | Nonnegativity (PARAFAC, PARAFAC2, Tucker): Why do I get negative scores when all modes are set to nonnegativity?]]
 
[[faq_what_are_relative_contributions | What are "Relative Contributions"?]]
 
==Command Line==
==Manual==
==GUI==
==Installation==
 
 
 
 
 
 
 
[[Category:FAQ]]

Revision as of 14:15, 29 November 2018

_

Importing / Exporting

How do I concatenate multiple files into a single DataSet?

How do I create a multivariate image from separate images?

How do I export PCA scores and loadings to a text file (to read into MS Excel, for example)?

How do I import three-way data into Solo or PLS_Toolbox?

Why can't I import a Horiba NGC file on my 64-bit computer?

Why can't SPCREADR read multiple files I've selected?

Why do some Excel files fail to import?

General

Can I do PARALIND in PLS_Toolbox?

Can I install PLS_Toolbox (or Solo) on more than one PC, such as on my desktop and laptop computer?

Can I use multiple class sets (categorical variables) together in a SIMCA, PLSDA, or LDA model?

Can you give me more information on the R-Squared statistic?

How are RMSEC and RMSECV related to R2Y and Q2Y I see in other software?

Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings?

Does the software stop working if my maintenance expires?

How and where do I report a problem with PLS_Toolbox?

How are T-contributions calculated?

How are the ROC curves calculated for PLSDA?

How are the error bars calculated for a regression model and can they be related to a confidence limit (confidence in the prediction)?

How can I improve performance with PLS_Toolbox and Matlab on the Mac platform?

How do I assign classes for samples in a DataSet?

How do I build a classification model from a class set other than the first?

How do I choose between the different cross-validation leave-out options?

How do I cite/reference Eigenvector?

How do I interpret the ROC curves and Sensitivity / Specificity plots from PLSDA?

How do I make a DataSet backwards compatible?

How do I obtain or use a recompilation license for PLS_Toolbox?

How do I use the "custom" cross-validation option?

I keep getting "out of memory" errors when analyzing my data. What can I do?

What can I do if I get a java.lang.OutOfMemoryError error?

Nonnegativity (PARAFAC, PARAFAC2, Tucker): Why do I get negative scores when all modes are set to nonnegativity?

What are "Relative Contributions"?

Command Line

Manual

GUI

Installation

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