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找到约 10,000 项符合「Problem」的源代码

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m demglm2.m

%DEMGLM2 Demonstrate simple classification using a generalized linear model. % % Description % The problem consists of a two dimensional input matrix DATA and a % vector of classifications T. The da
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txt dma.txt

WHAT IS D.M.A.? Consider the problem of moving a large amount of data to or from an I/O device. This requirment is commonly encountered in the operation of many peripheral devices (disk drives,
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c coloringmanuel.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: Coloring Idea and first implementation: Andreas
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c anagrammanuel.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: Anagram Idea and Implementation: Manuel Bleiche
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c calculatormanuel.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: Calculator Idea and first implementation: Hans
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c spreadsheetrolf.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: SpreadSheet Idea: Manuel Bleichenbacher, Head
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c spreadsheetcreate.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: SpreadSheet Idea and Implementation: Manuel Ble
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c spreadsheetmanuel.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: SpreadSheet Idea and Implementation: Manuel Ble
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c synchronousmanuel.c

/* 1995-96 ACM International Collegiate Programming Contest Southwestern European Regional Contest ETH Zurich, Switzerland December 9, 1995 Problem: Synchronous Idea and implementation: Manuel Ble
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m dd_ex1.m

% DD_EX1 % % Example of the creation of a One-Class problem, and the solutions % obtained by the Nearest Neighbor Data Description and the Support % Vector Data Description. Furthermore, the ROC curve