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Table 14 LDA Geometric shapes

From: Deriving image features for autonomous classification from time-series recurrence plots

Analyses

Hyper-plane side

LD1

LD2

LD3

LD4

STANDARD

-

- Compact

- HU1

- Compact

- Compact

- Eccentricity

- Solidity

- HU1

- HU1

+

- HU1

- Compact

- Solidity

- Solidity

- Homogeneity

- Homogeneity

RQA

-

- Laminarity

- Clustering coefficient

- Clustering coefficient

- Clustering coefficient

- Transitivity

- Determinism

- Laminarity

- Recurrence rate

+

- Determinism

- Laminarity

- Recurrence time 1

- Determinism

- Transitivity

- Determinism

- Recurrence period density

- Recurrence Rate

- Transitivity

- Transitivity

STANDARD & RQA

-

- Homogeneity

- Determinism

- Solidity

- Recurrence rate

- Clustering coefficient

- Compact

- Recurrence rate

- Transitivity

- Laminarity

- Homogeneity

- Clustering coefficient

- Laminarity

- Clustering coefficient

- Laminarity

- Recurrence time 1

+

- Eccentricity

- HU1

- Determinism

- Determinism

- Determinism

- Solidity

- Compact

- Compact

- Recurrence rate

- HU1

- HU1

- Transitivity

- Transitivity

- Recurrence rate

- Laminarity

- Transitivity

- Recurrence Time 1

STANDARD & RQA & ESQ

-

- HU1

- Determinism

- Solidity

- Recurrence rate

- Homogeneity

- Compact

- Recurrence rate

- Transitivity

- Clustering coefficient

- Homogeneity

- Clustering coefficient

- Laminarity

- Laminarity

- Clustering coefficient

- Laminarity

- Recurrence Time 1

+

- Eccentricity

- HU1

- Determinism

- Determinism

- Determinism

- Solidity

- Compact

- HU1

- Recurrence rate

- Recurrence rate

- HU1

- Transitivity

- Transitivity

- Transitivity

- Recurrence time 1

- Laminarity

  1. Importance of features included in LDA. Features were considered to be important when their loading reached at least 10 % of the maximum loading on the respective side of the hyperplane, set up by the discriminant roots (LD)