|
4071
|
C4.5: Programs for machine learning
– J Quinlan
- 1993
|
|
11
|
Extreme events from the return-volume process: a discretization approach for complexity reduction
– P Buhlmann
- 1998
|
|
42
|
Use of Contextual Information for Feature Ranking and Discretization
– Se June Hong
- 1997
|
|
3145
|
R.: Classification and Regression Trees
– L Breiman, J Friedman, C Stone, Olshen
- 1984
|
|
896
|
BD: Pattern Recognition and Neural Networks
– Ripley
- 1996
|
|
91
|
Error-Based and Entropy-Based Discretization of Continuous Features
– Ron Kohavi, Mehran Sahami
- 1996
|
|
332
|
Computer systems that learn
– S Weiss, C Kulikowski
- 1991
|
|
40
|
Optimized rule induction
– S Weiss, N Indurkhya
- 1993
|
|
1904
|
M.: Pricing of options and corporate liabilities
– F Black, Scholes
- 1973
|
|
21
|
Spatial Representation of Symbolic Sequences through Iterative Function Systems
– Peter Tino
- 1998
|
|
16
|
Forecasting volatility and option prices of the S&P500 index
– J —Noh, R F Engle, A Kane
- 1994
|
|
69
|
The Power of Amnesia
– Dana Ron, Yoram Singer, Naftali Tishby
- 1994
|
|
2726
|
Self-Organizing Maps
– T Kohonen
- 2000
|
|
337
|
Generalized Autoregressive Conditional Heteroscedasticity
– T Bollerslev
- 1986
|
|
682
|
The CN2 Induction Algorithm
– Peter Clark , Tim Niblett
- 1989
|
|
296
|
The multi-purpose incremental learning system aq15 and its testing application to three medical domains
– R Michalski, I Mozetic, J Hong, H Lavrac
- 1986
|
|
8
|
Use of Randomization to Normalize Feature Merits
– S. J. Hong, J. Hosking, S. Winograd, Se June Hong, J. R. M. Hosking, Shmuel Winograd
- 1996
|
|
10
|
RAMP: Rules Abstraction for Modeling and Prediction
– Chidanand Apte, C. Apte, S. J. Hong, Jorge Lepre, and Barry Rosen, S. Prasad, B. Rosen, Se June Hong, Jorge Lepre, Seema Prasad, Barry Rosen
- 1995
|
|
18
|
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
– Se June Hong
- 1997
|
