Titlebook: Advances on Data Mining: Applications and Theoretical Aspects; 11th Industrial Conf Petra Perner Conference proceedings 2011 Springer-Verla

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書目名稱Advances on Data Mining: Applications and Theoretical Aspects影響因子(影響力)




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書目名稱Advances on Data Mining: Applications and Theoretical Aspects被引頻次




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書目名稱Advances on Data Mining: Applications and Theoretical Aspects讀者反饋




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Petra PernerFast-track conference proceedings.State-of-the-art research.Up-to-date results

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Catalysts for Nitrogen Fixationts. By representing the data in a local subspace spanned by samples carefully chosen by Fisher’s feature weighting scheme, ALH attempts to search for optimal pruning parameters after large number of iterations. However, the feature weight scheme is less accurate in quantifying multi-class problems a

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Superoxide-Dependent Nitrogenase,on and the ranked regression methods have been developed. Both these methods are useful in modeling censored data used in survival analysis. Designing the interval regression models as well as the ranked regression models can be treated similarly as the problem of linear classifier designing and lin

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Alkane Activation by Pseudo-Metals given data points, allowing some points to be excluded as outliers. Whether or not a point is excluded, is governed by a slack variable. Mathematically, the values for the slack variables are obtained by minimizing a cost function that balances the size of the sphere against the penalty associated

四指套

NATO Science Partnership Subseries: 3mostly black box methods such as neural nets and support vector machines have been heavily used in technical domains, methods that have explanation capability are preferred in medical domains. Nowadays, data mining methods with explanation capability are also used for technical domains after more wo

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https://doi.org/10.1007/978-94-017-0982-8n-generative methods is proposed. Five well-know strong classifiers are used for the non-generative method and bagging was used for generative method. The performances of the five base classifiers, their ensembles based on bagging, and the proposed hybrid metaclassifier are compared using classifica

BIBLE

Catalytic Oxidation of Alcohols with O2,an insufficient number of examples makes the learned model and future prediction inaccurate, while acquiring more examples than necessary wastes time and money. Thus it is very important to estimate the number examples needed for learning algorithms in machine learning. However, most previous learni

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