Titlebook: Vegetation of the Earth and Ecological Systems of the Geo-biosphere; Heinrich Walter Book 19853rd edition Springer-Verlag Berlin Heidelber

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Heinrich Waltero quickly adapt the network behavior to different possible scenarios. In this context, the adoption of machine learning approaches to forecast the customer energy consumption is essential to optimize network planning operations, avoid unnecessary energy production, and minimize power shortages. Howe

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oExp, an OntoDM module which gives a more granular representation of a predictive modeling experiment and enables annotation of the experiment’s provenance, algorithm implementations, parameter settings and output metrics. This module is incorporated in SemanticHub, an online system that allows exec

SEMI

Heinrich Walterbiased and skewed towards the majority class, often produce sub-optimal results. However, if biased or unbalanced data is not processed appropriately, any information extracted from such data risks being compromised. Least Squares Support Vector Machines (LS-SVM) is known for its computational advan

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Heinrich Walter entries of an input matrix. It has many practical data-mining applications, as the related biclustering problem, such as gene module discovery in bioinformatics. It differs from the maximum-weighted submatrix coverage problem introduced in?[.] by the explicit formulation of disjunction constraints:

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大酒杯

Heinrich Walterpecified classification performance measure. Common generic approaches, that are usable with any classifier and any performance measure, are either slow like error reduction, or heuristics like uncertainty sampling. In contrast, our Probabilistic Active Learning (PAL) approach offers versatility, di

農(nóng)學(xué)

revent churn, but targeting the right customers on the basis of their historical profile is a difficult task. Companies usually have recourse to two data-driven approaches: churn prediction and uplift modeling. In churn prediction, customers are selected on the basis of their propensity to churn in

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Heinrich Walterr methods for studying consumer preferences/choices, namely conjoint analysis and discrete choice experiments. Chapter 1 continues with a description of the context of discrete choice experiments. Subsequently, the research problems and the objectives ofthis dissertation are discussed. The chapter c