Meanwhile covering algorithm is a supervised learning algorithm which requires a lot of labeled examples .

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A series of formulation and a supervised learning algorithm of multi-views subspace analysis were investigated and obtained .

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This paper proposes a method combining supervised learning with unsupervised method to conduct CWS which incorporates unsupervised segmentation into Conditional Random Fields ( CRFs ) .

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The system adopts supervised learning Naive Bayes as the categorization model and information gain as the feature selection .

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And raises a combined method which combines supervised learning method and semi-supervised learning method to drug name recognition .

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DSPE is a linear supervised learning method which can extract features effectively and has good robustness .

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Because of using the known model to predict new data Classification is a favourable supervised learning process .

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Compared with traditional supervised learning and unsupervised learning semi-supervised learning is in a rather new field .

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Comparing with the supervised learning it saves the cost of tagging samples .

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At present text categorization based on supervised learning is a mature technology to solve the problem .

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Compared to supervised learning unsupervised learning of a late start has greater space for its research .

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Other feedforward models and supervised learning models .

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In order to develop linear local tangent space alignment to supervised learning algorithm an algorithm called orthogonal discriminant linear local tangent space alignment is proposed .

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After supervised learning the visual network can extract image features and classify patterns .

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A new hybrid supervised learning control scheme is presented for continuous stirred tank reactor ( CSTR ) systems .

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Decomposition of SAR images ' mixed pixels based on supervised learning ICA algorithm

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Propose a new ensemble supervised learning algorithm following by feature selection that is suitable for high dimensional data .

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Constrained clustering and transductive learning mainly deal with learning problems between unsupervised learning and supervised learning .

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Common examples of supervised learning include classifying e-mail messages as spam labeling Web pages according to their genre and recognizing handwriting .

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An 3D Expression Generating Method Based on Morphing and Supervised Learning

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In Multi-Agent Systems supervised learning algorithms are widely used such as the Artificial Neuron Network and Decision Tree .

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Semi-supervised learning flourishes as it can circumvent the limitations of unsupervised learning and supervised learning .

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Supervised learning with the use of regression and classification networks with sparse data sets will be explored .

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Supervised learning is tasked with learning a function from labeled training data in order to predict the value of any valid input .

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In this thesis first of all the importance of supervised learning for feature extraction is discussed .

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A supervised learning evidence theory classifier is proposed to solve this problem .

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Lattice machine is a novel approach to supervised learning .

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Different kinds of Gaussian process classification methods compared with the traditional supervised learning .

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Unsupervised learning is used to adjust input weight values and supervised learning is utilized to adjust output weight values .

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A decade ago it was thought that supervised learning was the way to do this : A team of linguists created dictionaries and grammar rules and taught them to the computer .

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