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《Chemphyschem》2006,7(5):1149-1150
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In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression. 相似文献
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This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear
dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency
trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional
in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge
symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold
fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried
out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching
the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade
to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons
discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely
indicates a new science paradigm in the economy and society domains beyond physics.
相似文献
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Renato Bruni 《Annals of Operations Research》2007,150(1):79-92
The paper is concerned with the problem of binary classification of data records, given an already classified training set
of records. Among the various approaches to the problem, the methodology of the logical analysis of data (LAD) is considered.
Such approach is based on discrete mathematics, with special emphasis on Boolean functions. With respect to the standard LAD
procedure, enhancements based on probability considerations are presented. In particular, the problem of the selection of
the optimal support set is formulated as a weighted set covering problem. Testable statistical hypothesis are used. Accuracy
of the modified LAD procedure is compared to that of the standard LAD procedure on datasets of the UCI repository. Encouraging
results are obtained and discussed. 相似文献
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Peptides represent an extensive class of biologically active molecules. They may be used as leads in the development of novel therapeutic agents provided the pharmacophoric information present within them can be translated into non-peptide analogs that lack the peptide backbone and are stable to proteolysis. This is the rationale for peptidomimetic drug design. Frequently, the -turn has been implicated as a conformation important for biological recognition of peptides. Empirical evidence from known peptidomimetics, coupled with a theoretical model of peptide binding and the observation that glycine and proline residues are common within the -turn, has suggested the design of molecules to mimic placement of between two and four of the side-chains. The moderate number of different -turn conformations, combined with the combinatoric nature of side-chain selection complicates the procedure. In this paper, cluster analysis has been used to classify the arrangement of C_ atoms about the various fragments of the -turn. Recombination of the observed patterns provides a general model for the -turn which may be used as an effective screen for potential peptidomimetic scaffolds in chemical databases. 相似文献
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To avoid changes in the original As species distribution in natural water after sampling, a method of immediate separation
of As(V) by anion exchange at the sampling site was developed. The procedure consists of two steps. The total concentration
of arsenic is determined in one part of the water sample acidified on site. Another part of the water samples is pressed through
a column filled with an anion exchanger. The As(III) species that is not redox-stable remains in the effluent of the sorbents
column and can be analyzed with conventional methods after stabilization by addition of conc. HNO3. As(V) is sorbed by the exchanger material. The As(V) concentration can be calculated as the difference between Assol and As(III), neglecting very low contents of methylated species.
Oxidation of Fe(II) by air followed by co-precipitation of arsenic with iron hydroxide was applied in field experiments to
minimize the As concentration in seepage and mining water. 相似文献