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SAC
2006
ACM
16 years 23 days ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
PKDD
2000
Springer
116views Data Mining» more  PKDD 2000»
15 years 10 months ago
Prior Knowledge in Economic Applications of Data Mining
A common form of prior knowledge in economic modelling concerns the monotonicity of relations between the dependent and explanatory variables. Monotonicity may also be an important...
A. J. Feelders
154
Voted
ANLP
1992
85views more  ANLP 1992»
15 years 8 months ago
Learning a Scanning Understanding for "Real-world" Library Categorization
This paper describes, compares, and evaluates three different approaches for learning a semantic classification of library titles: 1) syntactically condensed titles, 2) complete t...
Stefan Wermter
CLASSIFICATION
2008
84views more  CLASSIFICATION 2008»
15 years 7 months ago
Degenerating Families of Dendrograms
Dendrograms used in data analysis are ultrametric spaces, hence objects of nonarchimedean geometry. It is known that there exist p-adic representations of dendrograms. Completed b...
Patrick Erik Bradley
EWCBR
2006
Springer
15 years 10 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore