Classification

XYOM ANALYZES, CLASSIFICATION

Input:

A single file containing data which may be:

  • Global size (one column matrix)
  • DISTANCES (square matrix),
    • Mahalanobis distances (i.e., Euclidean distances between …_DF.txt)
    • Euclidean distances between …_PC.txt
  • PRINCIPAL COMPONENTS (rectangular matrix)
  • TABLE (rectangular matrix)
    • matrix of traditional measurements, matrix of …_NEF,matrix of …_ORP, etc…)

Analyses:

  • if input data are labelled as TABLE
    • PCA (Principal Component Analysis)
  • if input data are labelled as PC
    • DA (Discriminant analysis), a DA always assumes the entry data are PC; it cuts the sequence of PC to the number of individuals in the smallest group, minus one.
    • Validated classification based on Maximum likelihood method (CCCMLi)
    • Validated classification based on Mahalanobis distance method (CCCMaha)
    • HC BOOTSTRAP (hierarchical clustering): single linkage algorithm, bootstraps of input data and resulting trees (See Couette et al,…)
  • if input data are labelled as DISTANCES (Mahalanobis, Euclidean)
  • if input data are labelled as Global size

Output:

  • Report:
    • HC: Newick format with bootstrap if input are PC.
    • Validated classification: scores of correct assignments
  • Graphic :
    • HC: Tree. Single linkage dendrogram if input are DISTANCES,
    • PCA, DA: factor map of first two multivariate factors
    • Oneway ANOVA: quantile boxes