搜索资源列表
knn
- knn分类算法,实现了knn分类算法,还不错-KNN categorization algorithm
KNN
- knn分类器原理实现,可等同于matlab自带KNN函数-knn classification principle to achieve, can be equated with matlab function comes KNN
knn
- 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。(Neighborhood algorithm, or K nearest neighbor (kNN, k-NearestNeighbor) classification algorithm is one of the simplest methods in data mining class
KNN
- k临近算法,用于数据分类,此代码为机器学习实战的学习代码(K near algorithm, for data classification, this code for machine learning combat learning code)
knn
- 经典的分类算法,可以完成基本的分类。。。(Classic classification algorithm, you can complete the basic classification...)
knn所涉及
- KNN是通过测量不同特征值之间的距离进行分类。它的的思路是:如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)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。K通常是不大于20的整数。KNN算法中,所选择的邻居都是已经正确分类的对象。该方法在定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。(NN is classified by measuring the distance between the different eigenvalues. It is
K近邻_KNN
- matlab的一份K邻近值KNN分类算法(A K neighbor value KNN classification algorithm for matlab)
knn
- 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 simples
kNN
- kNN,用来分类分类速度快 容易理解,上手容易(kNN,fast to classify easy to understand,welcome to download)
KNN
- K最邻近密度估计技术是一种分类方法,不是聚类方法。 不是最优方法,实践中比较流行。 通俗但不一定易懂的规则是: 1.计算待分类数据和不同类中每一个数据的距离(欧氏或马氏)。 2.选出最小的前K数据个距离,这里用到选择排序法。 3.对比这前K个距离,找出K个数据中包含最多的是那个类的数据,即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering metho
knnclassification
- KNN分类器,可用于信号分类,论文中使用过的(KNN classifier, can be used for signal classification, used in the paper)
knn_indian_pines
- KNN分类,图像处理,(kNN,k-NearestNeighbor),数据挖掘(k-NearestNeighbor is a kind of algorithm of Data mining)
KNN
- 最近邻学习算法,Python实现,最近邻规则分类(steps: In order to determine the unknown instance categories, with examples of all known categories as reference Parameter selection of K The calculation examples and all known examples of the unknown distance Choose the
KNN
- 在训练集中数据和标签已知的情况下,输入测试数据,将测试数据的特征与训练集中对应的特征进行相互比较,找到训练集中与之最为相似的前K个数据,则该测试数据对应的类别就是K个数据中出现次数最多的那个分类。(In the case where the training data and the tag are known, the test data is input, the characteristics of the test data are compared with the character
2、KNN学习
- KNN算法MATLAB仿真,KNN算法是经典的分类算法,是机器学习的基础算法(KNN algorithm, MATLAB simulation)
kNN
- K近邻算法,即是给定一个训练数据集,对新的输入实例,在训练数据集中找到与该实例最邻近的K个实例(也就是上面所说的K个邻居), 这K个实例的多数属于某个类,就把该输入实例分类到这个类中(K nearest neighbor algorithm function)
新建文本文档.zip
- KNN分类是一个懒惰的分类方法,以K为值,根据距离公式的一种分类方法(KNN classification is a lazy classification method, taking K as a value, and a classification method based on distance formula)
KNN
- 人工智能课程的KNN算法实现,包括回归和分类。(Artificial intelligence curriculum KNN algorithm, including regression and classification.)
新建文件夹
- 一个简单的分类器-KNN,可以很好地达到将几种属性分离开来。(A simple classifier, is a good way to achieve split several attributes.)
KNN
- 分类算法数字识别,KNN算法, 调用代码 import lyqKnn from numpy import * lyqKnn.handwritingClassTest()(Classification algorithm digital recognition)