Linear discriminant analysis with misallocation in training samples

By R. Chhikara, J. McKeon. 1984

How researchers see this paper

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

1. Richard J. Bolton
2. David J. Hand
3. Michel Verleysen
4. Benoît Frénay
5. Andrea Dal Pozzolo
6. Indrė Žliobaitė
7. Harald Steck
8. David S. Matteson

Citations in the corpus

• Learning kernel logistic regression in the presence of class label noise (2014, background): “Part of the reason for this may be that uniform/symmetric label noise is relatively harmless [21,22,12,27].”
• Classification in the Presence of Label Noise: A Survey (2014, background): “LDA is also studied in the presence of label noise by [72], which generalizes the results of [70], [71], [90]–[92].”
• Statistical fraud detection: A review (2002, background): “Some work has addressed misclassification of training samples (e.g., Lachenbruch, 1966, 1974; Chhikara and McKeon, 1984), but not in the context of fraud detection as far as we are aware.”