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» Learning of Boolean Functions Using Support Vector Machines
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2007
Springer
13 years 9 months ago
An Application of Machine Learning Methods to PM10 Level Medium-Term Prediction
The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants...
Giovanni Raimondo, Alfonso Montuori, Walter Moniac...
NN
2007
Springer
106views Neural Networks» more  NN 2007»
13 years 8 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi
ICMLA
2007
13 years 10 months ago
SVMotif: A Machine Learning Motif Algorithm
We describe SVMotif, a support vector machine-based learning algorithm for identification of cellular DNA transcription factor (TF) motifs extrapolated from known TF-gene interact...
Mark A. Kon, Yue Fan, Dustin T. Holloway, Charles ...
LWA
2004
13 years 10 months ago
A Simple Method For Estimating Conditional Probabilities For SVMs
Support Vector Machines (SVMs) have become a popular learning algorithm, in particular for large, high-dimensional classification problems. SVMs have been shown to give most accur...
Stefan Rüping
IJBRA
2010
133views more  IJBRA 2010»
13 years 6 months ago
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
Mona Soliman Habib, Jugal Kalita