... algorithm, originated from Widrow and Hoff’s
21 Neural Networks For Data Mining 429
in-sample and out-of-sample if the data size is very large. Typical split in data mining
applications reported in ... useful data mining model.
There are several practical issues around the data requirement for a neural net-
work model. The first is the data quality. As data sets used...
... in data mining, Data Mining and Knowledge Discovery, 15(1):87-97, 20 07.
Larose, D.T., Discovering knowledge in data: an introduction to data mining, John Wiley and
Sons, 20 05.
Maimon O., and ... Pub, 20 05.
Wu, X. and Kumar, V. and Ross Quinlan, J. and Ghosh, J. and Yang, Q. and Motoda, H. and
McLachlan, G.J. and Ng, A. and Liu, B. and Yu, P.S. an...
... Foundations and New Directions in Data Mining, as-
sociated with the third IEEE International Conference on Data Mining, Melbourne, FL,
November 1 922 , 24 –30, 20 03A.
Dardzinska A. and Ras Z.W. On rule discovery ... (Dardzinska and Ras, 20 03A,Dardzinska
and Ras, 20 03B).
Learning missing attribute values from summary constraints was reported in (Wu
and Barbara, 20 02...
... Springer, pp. 178-196, 20 02.
Maimon, O. and Rokach, L., Decomposition Methodology for Knowledge Discovery and
Data Mining: Theory and Applications, Series in Machine Perception and Artificial In-
telligence ... Kaufmann, 1996.
Maimon O., and Rokach, L. Data Mining by Attribute Decomposition with semiconductors
manufacturing case study, in Data Mining for Design and...
... Conference on Data- mining
(ICDM’ 02) , Maebashi City, Japan, CSIRO Technical Report CMIS- 02/ 1 02, 20 02.
Williams G. J., Huang Z., Mining the knowledge mine: The hot spots methodology for
mining large ... phenomena).
When data is limited, it is common practice to re-sample the data, that is, partition
the data into training and test sets in different ways. An inducer is tr...
... 131–158.
Rokach, L. and Maimon, O., Clustering methods, Data Mining and Knowledge Discovery
Handbook, pp. 321 –3 52, 20 05, Springer.
Rokach, L. and Maimon, O., Data mining for improving the quality of manufacturing: ... 14: 2, 24 1-301, 20 02.
Shafer, J. C., Agrawal, R. and Mehta, M. , SPRINT: A Scalable Parallel Classifier for Data
Mining, Proc. 22 nd Int. Conf...
... as:
d(x
i
,x
j
)=(w
1
x
i1
−x
j1
g
+ w
2
x
i2
−x
j2
g
+ +w
p
x
ip
−x
jp
g
)
1/g
where w
i
∈ [0,∞)
27 8 Lior Rokach
can be interpreted as agreements, and b and c as disagreements. The Rand index is
defined as:
RAND ... + b + c + d
The Rand index lies between 0 and 1. When the two partitions agree perfectly, the
Rand index is 1.
A problem with the Rand index is t...
... Kluwer.
Freitas AA (20 01) Understanding the crucial role of attribute interaction in data mining.
Artificial Intelligence Review 16(3), 177-199.
Freitas AA (20 02a) Data Mining and Knowledge Discovery with ... data mining: a position
paper. ACM SIGKDD Explorations, 6 (2) , 77-86, Dec. 20 04.
Freitas AA (20 05) Evolutionary Algorithms for Data Mining. In: O. Maimon and L...