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| | ===Purpose=== |
| ==Importing / Exporting== | |
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| [[faq_concatenate_multiple_files|How do I concatenate multiple files into a single DataSet?]]
| | Calculate Variable Importance in Projection from NPLS model. |
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| [[faq_create_multivariate_image_from_separate_images|How do I create a multivariate image from separate images?]]
| | ===Synopsis=== |
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| [[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)?]]
| | :vip_scores = vipnway(model) |
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| [[faq_import_three-way_data|How do I import three-way data into Solo or PLS_Toolbox?]]
| | ===Description=== |
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| [[faq_import_horiba_NGC_64bit |Why can't I import a Horiba NGC file on my 64-bit computer?]]
| | Variable Importance in Projection (VIP) scores estimate the importance of each variable in the projection used in a NPLS model and is often used for variable selection. A variable with a VIP Score close to or greater than 1 (one) can be considered important in given model. Variables with VIP scores significantly less than 1 (one) are less important and might be good candidates for exclusion from the model. It works for X n-way and Y up to two-way and it assume samples are in the first mode. |
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| [[faq_SPCREADR_cant_read_multiple_files |Why can't SPCREADR read multiple files I've selected?]]
| | ====Inputs==== |
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| [[faq_some_EXCEL_files_fail_to_import |Why do some Excel files fail to import?]]
| | * '''model''' = A NPLS model structure from a NPLS model. |
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| ==General== | | ====Outputs==== |
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| [[faq_PARALIND_in_PLS_Toolbox |Can I do PARALIND in PLS_Toolbox?]] | | * '''vip_scores''' = a cell array with dimensions of: [modes 2 to n X # of columns in Y]. The first row in the cell array corresponds to VIP Scores for mode 2. The second row corresponds to VIP Scores for mode 3. |
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| [[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?]]
| | ===See Also=== |
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| [[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?]] | | [[selectvars]], [[genalg]], [[ipls]], [[plotloads]], [[pls]], [[plsda]], [[sratio]], [[rpls]], [[vip]] |
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| [[faq_more_info_on_R_Squared_statistic | Can you give me more information on the R-Squared statistic?]] | |
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| [[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?]] | |
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| [[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?]] | |
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| [[faq_does_software_stop_working_if_maintenance_expires | Does the software stop working if my maintenance expires?]] | |
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| [[faq_report_a_problem_with_PLS_Toolbox | How and where do I report a problem with PLS_Toolbox?]] | |
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| [[faq_how_are_T_contributions_calculated | How are T-contributions calculated?]] | |
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| [[faq_how_are_ROC_curves_calculated_for_PLSDA | How are the ROC curves calculated for PLSDA?]]
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| [[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)?]]
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| [[faq_improve_performance_with_PLS_Toolbx_and_Matlab_on_Mac | How can I improve performance with PLS_Toolbox and Matlab on the Mac platform?]]
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| [[faq_assign_classes_for_samples_in_a_DataSet | How do I assign classes for samples in a DataSet?]]
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| [[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?]]
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| [[faq_choose_between_different_cross_validation_leave_out_options | How do I choose between the different cross-validation leave-out options?]]
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| [[faq_reference_Eigenvector| How do I cite/reference Eigenvector?]]
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| [[faq_interpret_ROC_curves_and_Sensitivity_Specificity_plots_from_PLSDA | How do I interpret the ROC curves and Sensitivity / Specificity plots from PLSDA?]]
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| [[faq_make_DataSet_backwards_compatible | How do I make a DataSet backwards compatible?]]
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| [[faq_obtain_or_use_recompilation_license_for_PLS_Toolbox | How do I obtain or use a recompilation license for PLS_Toolbox?]]
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| [[faq_use_custon_cross_validation_option | How do I use the "custom" cross-validation option?]]
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| [[faq_out_of_memory_error_when_analyzing_data | I keep getting "out of memory" errors when analyzing my data. What can I do?]]
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| [[faq_java_lang_OutOfMemoryError| What can I do if I get a java.lang.OutOfMemoryError error?]] | |
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| [[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?]]
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| [[faq_what_are_relative_contributions | What are "Relative Contributions"?]]
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| [[faq_what_are_reduced_T^2_and_Q_Statistics | What are the "Reduced" T^2 and Q Statistics?]]
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| [[faq_units_for_RMSEC_and_RMSECV_for_PLSDA | What are the units used for RMSEC and RMSECV when cross-validating PLSDA models? Why do the cross-validation curves look strange for PLSDA?]]
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| [[faq_what_do_the_four_Fit_/_Unique_Fit_stats_mean_in_MCR_PARAFAC | What do the four Fit/Unique Fit statistics mean in MCR and PARAFAC models?]]
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| [[faq_internal_tests_used_to_select_suggested_number_of_PCs | What internal tests are used to select "suggested" number of PCs?]]
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| [[faq_what_is_PLS1_v_PLS2_and_how_to_create_separate_PLS1_models_from_multi_column_y_block | What is PLS1 vs PLS2 and how do I create separate PLS1 models when I have a multi-column y-block?]]
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| ==Command Line==
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| ==Manual==
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| ==GUI==
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| ==Installation==
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| [[Category:FAQ]] | |
Purpose
Calculate Variable Importance in Projection from NPLS model.
Synopsis
- vip_scores = vipnway(model)
Description
Variable Importance in Projection (VIP) scores estimate the importance of each variable in the projection used in a NPLS model and is often used for variable selection. A variable with a VIP Score close to or greater than 1 (one) can be considered important in given model. Variables with VIP scores significantly less than 1 (one) are less important and might be good candidates for exclusion from the model. It works for X n-way and Y up to two-way and it assume samples are in the first mode.
Inputs
- model = A NPLS model structure from a NPLS model.
Outputs
- vip_scores = a cell array with dimensions of: [modes 2 to n X # of columns in Y]. The first row in the cell array corresponds to VIP Scores for mode 2. The second row corresponds to VIP Scores for mode 3.
See Also
selectvars, genalg, ipls, plotloads, pls, plsda, sratio, rpls, vip