{ "item_title" : "Case-Based Predictions", "item_author" : [" Gilboa Itzhak "], "item_description" : "The book presents an axiomatic approach to the problems of prediction, classification, and statistical learning. Using methodologies from axiomatic decision theory, and, in particular, the authors' case-based decision theory, the present studies attempt to ask what inductive conclusions can be derived from existing databases. It is shown that simple consistency rules lead to similarity-weighted aggregation, akin to kernel-based methods. It is suggested that the similarity function be estimated from the data. The incorporation of rule-based reasoning is discussed.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/81/436/617/981436617X_b.jpg", "price_data" : { "retail_price" : "137.00", "online_price" : "137.00", "our_price" : "137.00", "club_price" : "137.00", "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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