An extension of Fisher's discriminant analysis for stochastic processes

By Hyejin Shin. 2008

54 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/dc9108104a72628c11c28a51e83a0b0be51a1b8a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Aurore Delaigle
2. Peter Hall
3. N. Bathia
4. H. Muller
5. A. Meister
6. Han Lin Shang
7. Adela Martínez-Calvo
8. Yehua Li

In Control and Systems Engineering

1. Peter Hall
2. Aurore Delaigle
3. N. Bathia
4. H. Muller
5. Antonio Cuevas

In Statistics and Probability

1. Aurore Delaigle
2. Peter Hall
3. N. Bathia
4. H. Muller
5. Han Lin Shang
6. Antonio Cuevas
7. A. Meister
8. Wenceslao González-Manteiga

Citations in the corpus

• Achieving near perfect classification for functional data (2012, methodology): “It includes methodology that was suggested by James and Hastie (2001), Preda et al. (2007) and Shin (2008), who suggested linear discriminant analysis, Ferraty and Vieu (2003), who constructed classifiers based on kernel estimators of prior probabilities, James and Sugar (2003), who introduced…”
• Componentwise classification and clustering of functional data (2012, methodology): “…application of our methodology to five popular classifiers: Fisher’s linear and quadratic discriminants (James and Hastie, 2001; Preda et al., 2007; Shin, 2008), a nonparametric Bayes rule, a nonparametric regression-based classifier (Ferraty and Vieu, 2003, 2006) and a classifier based on…”