Description: 朴素贝叶斯(Naive Bayes, NB)算法是机器学习领域中常用的一种基于概率的分类算法，非常简单有效。k近邻法(k-Nearest Neighbor, kNN)[30,31]又称为基于实例(Example-based, Instance-bases)的算法，其基本思想相当直观：Rocchio法来源于信息检索系统，后来最早由Hull在1994年应用于分类[74]，从那以后，Rocchio方法就在文本分类中广泛应用起来。-Naive Bayes (Naive Bayes, NB) algorithm is commonly used in the field of machine learning a classification algorithm based on probability is very simple and effective. k neighbor method (k-Nearest Neighbor, kNN) [30,31], also known as case-based (Example-based, Instance-bases) of the algorithm, the basic idea quite intuitive: Rocchio law from the Information Retrieval System, and later was first proposed by the Hull in 1994, applies to classification [74], since then, Rocchio method of classification in the text with extensive application. Platform: |
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Author:许梁 |
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Description: 寻找测试样本的最近邻，可以有效的用于用于模式识别，信号处理-This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing.
The code was initially implemented through vectorization. After discussions with John D Errico, I realized that my algorithm will suffer numerical accurancy problem for data with large values. Then, after trying several approaches, I found simple loops with JIT acceleration is the most efficient solution. Now, the performance of the code is comparable with kd-tree even the latter is coded in a mex file.
The code is very simple, hence is also suitable for beginner to learn knn search. Platform: |
Size: 3072 |
Author:刘晓红 |
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Description: 自己编写的近邻法算法，包括k近邻法、两分剪辑和重复剪辑、压缩算法。在文档中给出了一个简单的算法原理说明，详细参考边肇的《模式识别》。注：里面的分类线绘制算法存在一些问题，仅供大家参考修改。-The nearest neighbor algorithm written by myself, including k nearest neighbor, the two sub-editing and re editing, compression algorithm. The document gives a simple algorithm principle . The detailed explanation can be found in the book Pattern Recognition written by Bian Zhaoqi. Note: The line drawing algorithms have some problems, only for your reference. Platform: |
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Author:陈章 |
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Description: This simple KNN algorithm implementation for Feature selection, written in C-This is simple KNN algorithm implementation for Feature selection, written in C++ Platform: |
Size: 259072 |
Author:melaning21 |
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Description: 实现knn算法，代码简单，通俗易懂，运行完全正确，支持k为任意整数 -Achieve knn algorithm code is simple, easy to understand, run entirely correct, supports k is any integer Platform: |
Size: 2048 |
Author:韩梅 |
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Description: knn算法的简单实现，需要测试两个文件，一个测试文档，一个是待分类文本-knn algorithm is simple to achieve, you need to test the two documents, a test document, a text is to be classified Platform: |
Size: 3072 |
Author:2006081224 |
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Description: 简单的 knn 文本算法 ，用于中文文本分类，比较方便的方法！-Simple text knn algorithm for Chinese text classification, more convenient way! Platform: |
Size: 8192 |
Author:hu |
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Description: 一个简单的knn算法程序，核心算法是基于欧几里得距离，程序在vs2010上调试运行，一点问题都没有，其他环境不知道-A simple knn algorithm program, the core algorithm is based on the Euclidean distance, program debugging run on vs2010, no problem at all, other environments do not know. Platform: |
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Author:yu |
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Description: 邻近算法，或者说K最近邻(kNN，k-NearestNeighbor)分类算法是数据挖掘分类技术中最简单的方法之一。所谓K最近邻，就是k个最近的邻居的意思，说的是每个样本都可以用它最接近的k个邻居来代表。
kNN算法的核心思想是如果一个样本在特征空间中的k个最相邻的样本中的大多数属于某一个类别，则该样本也属于这个类别，并具有这个类别上样本的特性。该方法在确定分类决策上只依据最邻近的一个或者几个样本的类别来决定待分样本所属的类别。 kNN方法在类别决策时，只与极少量的相邻样本有关。由于kNN方法主要靠周围有限的邻近的样本，而不是靠判别类域的方法来确定所属类别的，因此对于类域的交叉或重叠较多的待分样本集来说，kNN方法较其他方法更为适合。-Nearby algorithm, or K-nearest neighbor (kNN, k-NearestNeighbor) classification algorithm is one of classification data mining technology in the most simple way. The so-called K-nearest neighbor is the k nearest neighbors meant to say is that it can be used for each sample k nearest neighbors to represent. kNN algorithm core idea is that if a sample in feature space is k-nearest neighbor samples most belong to a category, the sample also fall into this category, and the category having the characteristics of the sample. The method in determining the classification decision based solely on the nearest one or several samples to determine the category to be sub-sample belongs to the category. kNN method when category decisions, with only a very small amount of adjacent samples related. Because kNN method is mainly limited by the surrounding adjacent samples, rather than the domain identification method to determine the class belongs to the category, so for class field of overlap or more s Platform: |
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Author:黑色地位 |
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Description: 这是一个简单的测试knn算法的代码，便于初学者学习和理解knn算法-This is a simple test knn algorithm code, for beginners to learn and understand knn algorithm Platform: |
Size: 2048 |
Author:杜凡 |
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Description: 这是我自己写的knn的算法，实现了聚类，比较简单-This is what I wrote it myself knn algorithm implements clustering, relatively simple Platform: |
Size: 232448 |
Author:xululu |
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Description: 运用java 语言简单实现knn算法，邻近算法，或者说K最近邻(kNN，k-NearestNeighbor)分类算法是数据挖掘分类技术中最简单的方法之一(Using java language simple implementation of KNN algorithm, neighbor algorithm, or K nearest neighbor (kNN, k-NearestNeighbor) classification algorithm is one of the simplest methods of data mining classification technology) Platform: |
Size: 2048 |
Author:武林至尊
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Description: 关于K近邻算法的简单实现和一些例子，其中包括手写数字的识别(Simple implementation of K nearest neighbor algorithm and some examples) Platform: |
Size: 350208 |
Author:Tony_siji |
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Description: 一个简单好用的KNN算法程序，只需要输入训练集和对应的标签就可以得到想要的模型并进行测试集的预测(A simple and easy-to-use KNN algorithm program only needs to input the training set and corresponding tags to get the desired model and predict the test set) Platform: |
Size: 292864 |
Author:INnoCeNcE* |
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Search - Simple KNN algorithm