搜索资源列表
knn
- 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。
billiner
- 一个用matlab编写的最近邻插值法求图像的范大于缩小的小程序
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
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
interpolation.rar
- 几种传统的图像插值放大方法:最近邻插值法,双线性插值法,双三次插值法,Several traditional interpolation to enlarge the image : nearest neighbor interpolation, bilinear interpolation, bicubic interpolation.
dance
- 此题是用最近邻域法实现图像缩放,供菜鸟练习用,这种算法不高清-This problem is the nearest neighbor domain method to achieve image scaling for the rookie practice with, this algorithm does not high-definition
project1
- 放大和缩小图像,采用最近邻域内插和像素复制法放大图像,采用像素删除法缩小图像-Zoom in and out using the nearest neighbor interpolation and pixel replication method to enlarge the image, pixel deletion method to reduce the image
空间插值方法汇总
- Inverse Distance to a Power(反距离加权插值法) Kriging(克里金插值法) Minimum Curvature(最小曲率) Modified Shepard s Method(改进谢别德法) Natural Neighbor(自然邻点插值法) Nearest Neighbor(最近邻点插值法) Polynomial Regression(多元回归法) Radial Basis Function(径向基
ClosestFacilitySolver
- ArcGIS Engine 二次开发,VBA语言,功能:实现网络分析中最近邻分析法。可以用于提取最短路径。-ArcGIS Engine secondary development, VBA language features: realization of network analysis in the nearest neighbor analysis. Can be used to extract the shortest path.
palmprint-recognition-
- 首先计算掌纹图像二维Gabo r小波变 换系数的幅值, 将其作为掌纹图像的原始特征 其次, 利用 2DPCA 实现原始特征的降维 然后, 利用PCA 与FLD 的融合算 法进行二次降维的同时提取出最有利于分类的鉴别特征 最后, 利用最近邻算法进行掌纹的分类识别。 -First calculate the two-dimensional Gabo r palmprint image wavelet coefficients of magnitude, its character
pr_basic_code
- 模式识别基本方法matlab源代码,包括最小二乘法、SVM、神经网络、1_k近邻法、剪辑法、特征选择和特征变换-Basic method of pattern recognition matlab source code, including the least squares method, SVM, neural networks, 1_k neighbor method, the clip method, feature selection and feature transformati
regress2beltak
- matlab实现使用统计学习基础中的最小二乘法和k-最近邻法进行分类。-matlab achieve statistical learning-based classification using the least squares method and k-nearest neighbor method.
nearest
- 最近邻法 matlab编写-Nearest neighbor method of matlab source code
eigenface
- 利用人脸pca进行数据压缩,形成人脸特征脸,然后用最近邻法进行人脸识别。-Face pca use data compression to form facial features face recognition and then the nearest neighbor method.
classification-Python
- python实现感知器、贝叶斯分类、决策树分类、K最近邻法、逻辑回归、支持向量机-Python implementation of perceptron, Bias classification, decision tree classification, K nearest neighbor method, logic regression, support vector machine
jinlin
- 最近邻法,K-近邻法,剪辑近邻法和压缩近邻法。模式识别-Nearest neighbor, K- nearest neighbor, editing and compression nearest neighbor nearest neighbor method. Pattern Recognition
k-nearest-neighbors
- k最近邻法、有权重的k最近邻法及线性判别-K-nearest neighbor and linear discriminant analysis
类比法
- 型的类比学习方法是K-最近邻方法,它属于懒散学习法,相比决策树等急切学习法,具有训练时间短,但分类时间长的特点。K-最近邻算法可以用于分类和聚类中(The analogy learning method is K- nearest neighbor method. It belongs to the lazy learning method. Compared with the decision tree learning method, it has the characteristics o
三步搜索法
- 本实验的目的是学习Parzen窗估计和k最近邻估计方法。在之前的模式识别研究中,我们假设概率密度函数的参数形式已知,即判别函数J(.)的参数是已知的。本节使用非参数化的方法来处理任意形式的概率分布而不必事先考虑概率密度的参数形式。在模式识别中有躲在令人感兴趣的非参数化方法,Parzen窗估计和k最近邻估计就是两种经典的估计法。(The purpose of this experiment is to study the Parzen window estimation and the k nea
最近邻卡尔曼滤波
- 采用最近临近法,结合卡尔曼滤波,进行目标跟踪,但是不能在杂波环境下(Using the recent approach, combined with Kalman filter, the target tracking, but not in the clutter environment)