代码搜索:classification

找到约 3,679 项符合「classification」的源代码

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m getbias.m

function bias = getbias(net) % GETBIAS % % Accessor method returning the bias of a support vector classification % network. % % bias = getbias(net); % % File : @svc/getbias.m %
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m svctutor.m

function tutor = svctutor(arg) % SVCTUTOR % % Constructor for a class of tutor objects used to train support vector % classification networks. Note this is an abstract base class, you cannot %
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m demtrain.m

function demtrain(action); %DEMTRAIN Demonstrate training of MLP network. % % Description % DEMTRAIN brings up a simple GUI to show the training of an MLP % network on classification and regression pr
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py tree4.py

# Author: J Zabkar # Version: 1.0 # Description: Storing and printing out the examples in classification tree # Category: modelling # Uses: iris.tab # Referenced: orngTree.ht
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py accuracy2.py

# Description: Set a number of learners, for each build a classifier from the data and determine classification accuracy # Category: evaluation # Uses: voting.tab # Referenced: c_perform
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py imputation.py

# Description: Shows the use of classes for imputation # Category: default classification accuracy, statistics # Classes: Imputer, Imputer_defaults, Imputer_asValue, Imputer_model, ImputerCon
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h example.h

/* Example.H * * An example is an assignment of values to each possible attribute. * An example has a name, and also a classification value. */ /* * Copyright 1994, Brown University, Providence,
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c example.c

/* Example.C * * An example is an assignment of values to each possible attribute. * An example has a name, and also a classification value. */ /* * Copyright 1994, Brown University, Providence,
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h example.h

/* Example.H * * An example is an assignment of values to each possible attribute. * An example has a name, and also a classification value. */ /* * Copyright 1994, Brown University, Providence,
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c example.c

/* Example.C * * An example is an assignment of values to each possible attribute. * An example has a name, and also a classification value. */ /* * Copyright 1994, Brown University, Providence,