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Wed Aug 27

• stock.xchng - tutorials
• 5203_235_ALEPS .pdf (application/p df-Objekt)
• Legende von der Erschaffung der Krankenschwest er
• Neighborhood size selection in the k-nearest-neig hbor rule using statistical confidence: doi:10.1016/j. patcog.2005.08 .009 Abstract. The k-nearest-neig hbor rule is one of the most attractive pattern classification algorithms. In practice, the choice of k is determined by the cross-validati on method. In this work, we propose a new method for neighborhood size selection that is based on the concept of statistical confidence. We define the confidence associated with a decision that is made by the majority rule from a finite number of observations and use it as a criterion to determine the number of nearest neighbors needed. The new algorithm is tested on several real-world datasets and yields results comparable to the k-nearest-neig hbor rule. However, in contrast to the k-nearest-neig hbor rule that uses a fixed number of nearest neighbors throughout the feature space, our method locally adjusts the number of nearest neighbors until a satisfactory level of confidence is reached. In addition...
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• Fresh Intelligence : Radar Online : The Ten Worst Twitters You'll Meet In Internet Hell
• Free Layer Mask Tool for Photoshop Elements
• Argus appareil photo numerique d'occasion

Tue Aug 26

• 45 Beautiful Motion Blur Photos | Monday Inspiration | Smashing Magazine
• Domínio Público - Pesquisa Básica

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