Results of PCA

Results of Cubatch are mainly graphical (to have main numerical results, see report in the menu file). Here is an overview of what is displayed after a PCA model.

Mode i: Loadings of the corresponding modes (1,2, or 3D plots)

Batch data: different colors for groups (when multiple sets, for example batch data)

Tools:

• Process control (available for 2D plots)
  • Hotelling's T² ellipsoïd: confidence region.
  • Potential functions: trace an estimated density of the probability of the points of the plot.
• Quality index: represents only points which are sufficiently representative (i.e. good explained variation).

Format:

• Continuous: points are connected.
• Discrete: points are not connected.

• Integer.
• Label.
• Marker.

Preferences:

• Color
• Marker
• Line style
• Grid
• Visible: when ubchecked, the learning cloud becomes unvisible.
• options of tools:
  • Hotelling's T² ellipsoïd:
    • Confidence levels.
    • Size: number of dots for the ellipse.
  • Potential contour:
    • Confidence levels.
    • Size: number of dots for the ellipse.

Explained variance

Plot of the core and representation of the importance of n-uplets of tucker model.

Qualities of modalities

• Explained variance (angle)
• SSE (distance)
• T² Hotelling statistic (proximities of modalities comparate to the learning cloud).

Model

Representation of the Tucker model.

Residuals

Representation of the residuals of the Tucker model.