{ "item_title" : "Parallel Implementation of an Artificial Neural Network Integrated Feature and Architecture Selection Algorithm", "item_author" : [" Craig W. Rizzo "], "item_description" : "The selection of salient features and an appropriate hidden layer architecture contributes significantly to the performance of a neural network. A number of metrics and methodologies exist for estimating these parameters. This research builds on recent efforts to integrate feature and architecture selection for the multi-layer perceptron. In the first stage of work a current algorithm is developed in a parallel environment, significantly improving its efficiency and utility. In the second stage, improvements to the algorithm are proposed. With regards to feature selection, a common random number (CRN) addition is presented. Two new methods of architecture selection are examined, including an information criterion and a signal-to-noise based procedure. These methodologies are shown to improve algorithm performance.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/28/830/681/1288306814_b.jpg", "price_data" : { "retail_price" : "15.95", "online_price" : "15.95", "our_price" : "15.95", "club_price" : "15.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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