📄 knn.h
字号:
// Copyright (C) 2003 Samy Bengio (bengio@idiap.ch)
//
// This file is part of Torch 3.
//
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
// 3. The name of the author may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef KNN_INC
#define KNN_INC
#include "Machine.h"
#include "DataSet.h"
namespace Torch {
/** This machine implements the K-nearest-neighbors (KNN) algorithm.
Given a dataset (in the constructor), the #forward# method returns
for a given input the average of the outputs of the K nearest examples
(in the input space, using the Euclidean distance). As a side effect,
the machine also keep the table of distances of the K-nearest-neighbors.
@author Samy Bengio (bengio@idiap.ch)
*/
class KNN : public Machine
{
public:
/// The number of nearest neighbors. Controls the capacity of the machine
int K;
/// For each nearest neighbor, keeps its distance to the current input
real* distances;
/// For each nearest neighbor, keeps its index in the dataset
int* indices;
/// The dataset that contains the potential neaghbors
DataSet* data;
/// the size of the output vector
int n_outputs;
/// the indices of the training examples
int *real_examples;
int n_real_examples;
///
KNN(int n_outputs_,int K_);
virtual void forward(Sequence *inputs);
virtual void setDataSet(DataSet *dataset_);
/// change the value of K
virtual void setK(int K_);
virtual ~KNN();
};
}
#endif
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -