نتایج جستجو برای: boosting spirit of collectivism

تعداد نتایج: 21166601  

Journal: :British Journal of Sports Medicine 2000

Journal: :مجله دانشکده حقوق و علوم سیاسی 0
دکتر علی اسلامی پناه هادی کریمی

the two parts of a lease contract cannot always assign the period of lease. sometimes it isn't mentioned any period in contract but they assert the smallest unit of time for assignment of the rental. therefore the civil low makes reputable the lease contracts that the period of rent is left unsaid in them for the same smallest unit of time. in 'spite of that the legal spirit of this a...

Journal: :Statistics and Computing 2010
Peter Bühlmann Torsten Hothorn

We propose Twin Boosting which has much better feature selection behavior than boosting, particularly with respect to reducing the number of false positives (falsely selected features). In addition, for cases with a few important effective and many noise features, Twin Boosting also substantially improves the predictive accuracy of boosting. Twin Boosting is as general and generic as boosting. ...

2002

Hegel's goal in his philosophy of subjective spirit is an empirically sensitive yet basically a priori science of mind. That sounds oxymoronic: How can a discipline be at once a priori and empirically sensitive? Here the elaborate structure of the Hegelian system serves a clear purpose. We have, first of all, the logic—the a priori element in all thought. The system's following two parts, the p...

2000
Marina Skurichina Robert P. W. Duin

To improve weak classifiers bagging and boosting could be used. These techniques are based on combining classifiers. Usually, a simple majority vote or a weighted majority vote are used as combining rules in bagging and boosting. However, other combining rules such as mean, product and average are possible. In this paper, we study bagging and boosting in Linear Discriminant Analysis (LDA) and t...

Journal: :Concrete Journal 2013

2001
Gunnar Rätsch

In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules – also called base hypotheses. The so-called boosting algorithms iteratively find...

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