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» Unsupervised feature selection using a neuro-fuzzy approach
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IJCAI
2007
15 years 1 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
15 years 9 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
ESANN
2006
15 years 1 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
ICIP
2006
IEEE
16 years 1 months ago
Perceptual Feature Selection for Semantic Image Classification
Content-based image retrieval has become an indispensable tool for managing the rapidly growing collections of digital images. The goal is to organize the contents semantically, a...
Dejan Depalov, Thrasyvoulos N. Pappas, Dongge Li, ...
VLSISP
2010
191views more  VLSISP 2010»
14 years 6 months ago
Sign Language Phoneme Transcription with Rule-based Hand Trajectory Segmentation
A common approach to extract phonemes of sign language is to use an unsupervised clustering algorithm to group the sign segments. However, simple clustering algorithms based on dis...
W. W. Kong, Surendra Ranganath