代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/400576/11573589
m dd_error.m
function [e,f] = dd_error(x,w)
%DD_ERROR compute false negative and false positive for oc_classifier
%
% E = DD_ERROR(X,W)
% E = DD_ERROR(X*W)
% E = X*W*DD_ERROR
%
% Compute the fraction of targ
www.eeworm.com/read/253950/12174155
htm knnfwd.htm
Netlab Reference Manual knnfwd
knnfwd
Purpose
Forward propagation through a K-nearest-neighbour classifier.
Synopsis
www.eeworm.com/read/150905/12250341
htm knnfwd.htm
Netlab Reference Manual knnfwd
knnfwd
Purpose
Forward propagation through a K-nearest-neighbour classifier.
Synopsis
www.eeworm.com/read/213240/15140075
m dd_error.m
function [e,f] = dd_error(x,w)
%DD_ERROR compute false positive and false negative for oc_classifier
%
% E = DD_ERROR(X,W)
% E = DD_ERROR(X*W)
% E = X*W*DD_ERROR
%
% Compute the fraction of targ
www.eeworm.com/read/316872/3602617
h pkt_cls.h
#ifndef __NET_PKT_CLS_H
#define __NET_PKT_CLS_H
#include
#include
#include
#include
/* Basic packet classifier frontend de
www.eeworm.com/read/414826/2141912
tcl s3.tcl
source mobile_node.tcl
source aodvnode.tcl
Trace set show_tcphdr_ 1
LL set delay_ 5us
Agent/TCP set packetSize_ 1460
NetHold set offset_ [Classifier set offset_]
NetHold set shift_ [Class
www.eeworm.com/read/396844/2407743
m knn_old.m
function [Class,P]=knn_old(Data, Proto, proto_class, K)
%KNN_OLD A K-nearest neighbor classifier using Euclidean distance
%
% [Class,P]=knn_old(Data, Proto, proto_class, K)
%
% [sM_class,P]=knn_old
www.eeworm.com/read/294611/8216514
m knn_old.m
function [Class,P]=knn_old(Data, Proto, proto_class, K)
%KNN_OLD A K-nearest neighbor classifier using Euclidean distance
%
% [Class,P]=knn_old(Data, Proto, proto_class, K)
%
% [sM_class,P]=knn_old
www.eeworm.com/read/367875/9724810
m knn_old.m
function [Class,P]=knn_old(Data, Proto, proto_class, K)
%KNN_OLD A K-nearest neighbor classifier using Euclidean distance
%
% [Class,P]=knn_old(Data, Proto, proto_class, K)
%
% [sM_class,P]=knn_old
www.eeworm.com/read/235928/14041387
m knn_old.m
function [Class,P]=knn_old(Data, Proto, proto_class, K)
%KNN_OLD A K-nearest neighbor classifier using Euclidean distance
%
% [Class,P]=knn_old(Data, Proto, proto_class, K)
%
% [sM_class,P]=knn_old