Graphics Reference
In-Depth Information
development of ensemble methods still leaves room for enhancements or new plots.
For exploratory work it is of benefit to have a big toolbox to choose from;for presen-
tation graphics it is important to have the ability to display the “key point” we want
to convey.
References
Breiman, L. (
). Bagging predictors, Machine Learn
(
):
-
.
Breiman, L.(
).Random forests-randomfeatures, Technical Report TR
,Uni-
versity of California-Berkeley, Statistics Department.
Breiman, L., Friedman, J., Olshen, R. and Stone, C. (
). Classification and Regres-
sion Trees,Wadsworth.
Forina, M., Armanino, C., Lanteri, S. and Tiscornia, E. (
). Classification of olive
oils from their fatty acid composition, in Martens, H. and Russwurm, H. (eds),
Food Research and Data Analysis, Applied Science, London, pp.
-
.
Harrison, D. and Rubinfeld, D. (
). Hedonic prices and the demand for clean air,
J Environ Econ Manage
:
-
.
Mangasarian, O. and Wolberg, W. (
).Cancer diagnosis via linear programming,
SIAM News
(
):
-
.
Ripley,B.(
).Pattern Recognition and Neural Networks,CambridgeUniversity
Press, Cambridge, UK.
Urbanek, S. (
). Interactive construction and analysis of trees, Proceedings of the
Joint Statistical Meetings,D.P.Mira(CD-ROM).
