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» Evaluating learning algorithms and classifiers
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IJIT
2004
15 years 5 months ago
Improving the Convergence of the Backpropagation Algorithm Using Local Adaptive Techniques
Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This articl...
Z. Zainuddin, N. Mahat, Y. Abu Hassan
ICIP
1998
IEEE
16 years 5 months ago
Color Pixels Classification in an Hybrid Color Space
In this paper, we describe a new approach for color image segmentation which is considered as a problem of pixels classification. The algorithm is applied to classify pixels of so...
Jack-Gérard Postaire, Ludovic Macaire, Nico...
CASCON
2001
148views Education» more  CASCON 2001»
15 years 5 months ago
Email classification with co-training
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
Svetlana Kiritchenko, Stan Matwin
ML
2000
ACM
105views Machine Learning» more  ML 2000»
15 years 4 months ago
Multiple Comparisons in Induction Algorithms
Abstract. A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction ...
David D. Jensen, Paul R. Cohen
CEC
2009
IEEE
15 years 11 months ago
Multi-objective optimization using self-adaptive differential evolution algorithm
- In this paper, we propose a Multiobjective Self-adaptive Differential Evolution algorithm with objective-wise learning strategies (OW-MOSaDE) to solve numerical optimization pr...
Vicky Ling Huang, Shuguang Z. Zhao, Rammohan Malli...