Download 1954 Chevrolet Advance-Design Trucks. For Loads of Value PDF

;1954 Chevrolet Advance-Design vans. For a great deal of worth ТЕХНИКА, ХОББИ и РАЗВЛЕЧЕНИЯ, ХОББИ и РЕМЕСЛА Название: 1954 Chevrolet Advance-Design vans. For a great deal of price Автор: - Издательство: - Год: 1953 Страниц: forty Формат: pdf Размер: 18,9 MбОфициальный рекламный проспект, посвященный коммерческим автомобилям и школьным автобусам Chevrolet 1954 модельного года: Chevrolet 1500, Chevrolet 3100, Chevrolet 3600, Chevrolet 3800, Chevrolet 4100, Chevrolet 4400, Chevrolet 6100, Chevrolet 6400, Chevrolet 6500, Chevrolet 5100, Chevrolet 5400, Chevrolet 5700 и их модификациям. eighty five

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1984)]. 5 and CART). Other inducers perform only the growing phase. 2 presents a typical algorithmic framework for top-down inducing of a decision tree using growing and pruning. Note that these algorithms are greedy by nature and construct the decision tree in a topdown, recursive manner (also known as “divide and conquer“). In each iteration, the algorithm considers the partition of the training set using the outcome of a discrete function of the input attributes. The selection of the most appropriate function is made according to some splitting measures.

Instances are classified by navigating them from the root of the tree down to a leaf, according to the outcome of the tests along the path. 3 (whether or not a potential customer will respond to a direct mailing). Internal nodes are represented as circles whereas leaves are denoted as triangles. The node “Last R” stands for the attribute “Last Reaction”. Note that this decision tree incorporates both nominal and numeric attributes. Given this classifier, the analyst can predict the response of a potential customer (by sorting it down the tree), and understand the behavioral characteristics of the potential customers regarding direct mailing.

Using a t-test on the generalization error produced on each fold has a lower chance of Type I error but may not give a stable estimate of the generalization error. It is common practice to repeat n fold crossvalidation n times in order to provide a stable estimate. However, this of course renders the test sets non-independent and increases the chance of Type I error. Unfortunately, there is no satisfactory solution to this problem. Alternative tests suggested by [Dietterich (1998)l have low chance of Type I error but high chance of Type I1 error - that is, failing t o identify a significant difference when one does actually exist.

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