搜索资源列表
knn_demo
- K近邻法的matlab程序，发现大家都在找它！-K-nearest neighbor method of Matlab procedures, I found that we all have to find it!
PatternRecognition
- 1.Fisher分类算法 2.感知器算法 3.最小二乘算法 4.快速近邻算法 5.K-近邻法 6.剪辑近邻法和压缩近邻法 7.二叉决策树算法
Parzen_KNN
- Parzen 窗 和 K近邻法进行概率密度估计 还带一个示波器控件.-Parzen window and K-nearest neighbor method probability density is estimated to bring an oscilloscope control.
混沌时间序列预测
- 1、该工具箱包括了混沌时间序列分析与预测的常用方法,有: (1)产生混沌时间序列(chaotic time series) Logistic映射 - \ChaosAttractors\Main_Logistic.m Henon映射 - \ChaosAttractors\Main_Henon.m Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m Duffing吸引子 - \ChaosAttractors\Main_Duffing.m Duffin
matlab K近邻分类法
- matlabK近邻法实现
2rar.rar
- 用matlab写的最近邻和K近邻法分类器，简单易懂，适合初学者,Written with matlab and K-NN nearest neighbor classifier, easy to understand for beginners
knn
- knn-K近邻法实现两分类的函数代码，输入为两类的样本特征，和待测试的样本向量，输出为分类结果。-knn-K nearest neighbor method to achieve the two categories of function code, enter the characteristics of two types of samples, and samples to be tested vector, the output for the classification.
KNearestCls
- 模式识别中的K近邻法和快速K近邻法的VC＋＋实现-Pattern Recognition and rapid K neighbors K neighbors law VC to achieve
linjin
- 用k近邻法和剪辑近邻法分类样本点，模式识别实验内容之一-K neighbors with neighbors and editing sample points classification, pattern recognition one experiment
KNN
- 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 giv
K近邻法
- K近邻法对Iris数据分类，输入分类结果和准确率。-K-nearest neighbor method for Iris data classification, enter the classification results and accuracy.
knn
- 模式识别 K近邻法实现，用c实现-K-nearest neighbor method, Pattern Recognition implementation
KClassify
- 使用K近邻法设计分类器，对一组数据进行分类-K-nearest neighbor algorithm to design the classifier, to classify a set of data
K-negibour-method
- 利用K近邻法实现数字识别算法。误差小，识别效率高，网络训练速度快。-K-nearest neighbor algorithm, digital identification algorithm. Error is small, high recognition efficiency and speed of network training.
k-iris
- 模式识别中用于完成数据的分类而用到的一种方法-k近邻。是将已有数据划分到3个类中，本方法中解决数据Iris数据的划分问题。将150个4维数据划分到3类。K近邻法是求最近的K个元素从而将其划分到已有类中。-Pattern recognition for the completion of the classification of the data used in a way-k neighbors. The existing data are divided into three classes
k-meas
- k近邻法分类iris数据。iris数据共分三类，每一类50个数据，这里把每一类前20个作为训练样本，后30个作为测试样本-k-nearest-neighbor classification iris data. iris data is divided into three categories, each category of data from 50, as the training samples in each category of the top 20 after 30 as th
K-means-IRIS
- 用平均值取代表点的方法和K近邻法对Iris花进行分类-With the average of the representative point method and K-nearest neighbor to classify Iris flower
pattern recognition
- 模式识别，fisher判别法，近邻法，k近邻法matlab例程(Pattern recognition, Fisher discriminant method, nearest neighbor method, k nearest neighbor method, matlab)
李航_统计学习方法
- 《统计学习方法》是计算机及其应用领域的一门重要的学科。《统计学习方法》全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。(The statistical learning method is an important subject in the field of computer and its application.)
鸢尾花分类
- 使用四种方法进行鸢尾花分类：最小距离分类器，K 近邻法，感知器，Fisher 准则。(Four methods are used to classify iris: minimum distance classifier, K-nearest neighbor method, perceptron and Fisher criterion.)