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Analysis > Dimension Reduction > Diagnostic > Component PlotCreate > Dimension Reduction > Plot > Component Plot. Then in the newly created component plot, view

appendPage("TitleOnly"); } new_output.subItems[0].text = "Component Plot"; new_output.name = "Component Plot"; var component_plot = new_output.appendR(r_expr); selected_group

plot <- ScreePlot(QInputs(inputItem)) Dimension Reduction - Diagnostic - Component Plot Dimension Reduction - Diagnostic - Goodness of Fit Plot Dimension

Analysis > Dimension Reduction > Diagnostic > Goodness of Fit PlotCreate > Dimension Reduction > Diagnostic > Goodness of Fit Plot Under Inputs > Dimension Reduction

'mcaObj']); Dimension Reduction - Diagnostic - Component Plot Dimension Reduction - Diagnostic - Scree Plot Dimension Reduction - Principal Components Analysis

subset = QFilter) Dimension Reduction - Diagnostic - Component Plot Dimension Reduction - Diagnostic - Scree Plot Dimension Reduction - Save Variable(s)

Add the object: In Displayr: Insert > More > Dimension Reduction > t-SNE In Q: Create > Dimension Reduction > t-SNE Under Inputs > Algorithm keep t-SNE

men Anything > Advanced Analysis > Dimension Reduction > Multidimensional Scaling (MDS)Create > Dimension Reduction > Multidimensional Scaling (MDS) Under

es")), subset = QFilter) Dimension Reduction - Principal Components Analysis Dimension Reduction - t-SNE Dimension Reduction - Multidimensional Scaling

a classification tree. Dimension Reduction Tools for reducing multi-dimensional data. For example, perform a Principal Components Analysis. Analysis of

distance plot, Cook's distance vs leverage plot, Influence index plot, Normal Q-Q plot, Residuals vs fitted plot, Residuals vs leverage plot, Scale-location

The dimension reduction method used to group and position the tokens. Details about parameters controlling the algorithm can be found in Dimension Reduction

object: In Displayr: Insert > More > Dimension Reduction > Multiple Correspondence Analysis In Q: Create > Dimension Reduction > Multiple Correspondence Analysis

Modify Labels. Menu renamed to Modify Tables or Plots. Menu renamed to Modify the Whole Table or Plot. Menu renamed to Recode. Menu renamed

041 Dimension 7 .190 .036 .020 Standard Coordinates: Observations Dimension 1 Dimension 2 Dimension 3 Dimension 4 Dimension 5 Dimension 6 Dimension 7 1

virture of the yml file. let scree_plot = selected_group.appendStandardR("Dimension Reduction - Diagnostic - Goodness of Fit Plot", {"inputItem": selected_item

Select Create > Dimension Reduction > Map... to create a map of a table. An expert system selects an appropriate algorithm. The algorithms available

Analysis, TURF - Incrementality Plot and TURF - Upset Plot Standard R features. TURF, Dimension Reduction - Principal Components Analysis, t-SNE, Multidimensional