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.