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code_1
- 在机器学习中利用欧氏距离设计一个KNN分类器，实现五折交叉验证，并用PCA进行降维-Develop a k-NN classifier with Euclidean distance and simple voting.Perform 5-fold cross validation, find out which k performs the best (in terms of accuracy)。Use PCA to reduce the dimensionality to 6, then p
Desktop
- 贝叶斯分类器的分类原理是通过某对象的先验概率，利用贝叶斯公式计算出其后验概率，即该对象属于某一类的概率，选择具有最大后验概率的类作为该对象所属的类-Bayesian classifier classification principle is a priori probability of an object by using the Bayesian formula to calculate the probability of subsequent experience, that is,
a1
- 学习模式识别的基本知识，经典的贝叶斯分类器，已经测试通过-Learn the basics of pattern recognition, the classic Bayesian classifier has been tested by
rosenblatt
- matlab实现了Rosenblatt分类器，其中包括了生成随机数据的函数，以及主要算法，可以直接执行。-matlab implements Rosenblatt classifier, including function, and the main algorithm to generate random data can be directly d.
rotation--forest
- 一些最新的旋转森林集成分类器的研究，能够很好的运用到高光谱图像、生物信息等其他方向。-Some of the latest research rotation forest integrated classifier, can be well applied to the other direction hyperspectral image, biological information.
BPrengongshenjingwangluo
- 人工神经网络的仿真 分类器 BPwangluo-rengongshenjign wangluo fenleiqi
Knn
- Knn源码，k最邻近方法，是一种统计分类器，属于惰性学习，对于包含数据特征变量筛选尤其有效-Knn source, k nearest neighbor method is a statistical classifier learning are inert, it contains the data for the characteristic variable filter is especially effective
LibSVMsharp-master
- C#版SVM分类器源代码包，包含源代码，测试程序，测试数据，可完美运行。-C# Version SVM classification source code ,include source code ,test procedure and test data ,it can be run perfectly.
chapter_GA
- SVM的参数优化——如何更好的提升分类器的性能-SVM parameter optimization- how to better enhance the performance of classifiers
Ch02
- 利用Python语言设计knn近邻算法分类器，包括测试算法数据以及成功应用该算法-KNN near neighbor classifier，demo
Ch03
- 这是《机器学习实战》中，讲述的决策树，运用Python语言设计决策树分类器，完全可以应用该算法-decision tree classification，demo
MKSVM
- 模糊支持向量机的代码程序,代码包含了多分类的分类器-The Fuzzy SVM
demoadaboost
- Adaboost是一种迭代算法，其核心思想是针对同一个训练集训练不同的分类器(弱分类器)，然后把这些弱分类器集合起来，构成一个更强的最终分类器（强分类器）。-Adaboost is an iterative algorithm, the core idea is the same for a training set different classifiers (weak classifiers), and then set up these weak classifiers to form a
adaboost
- adboost分类器 matlab源程序 用于训练样本 实现分类-Adaboost classifier Matlab source for training samples to achieve classification
Fisher-classification
- 这是Fisher线性判别分类器，对一般的图像分类效果不错-This is the Fisher linear discriminant classifier, the general image classification effect is good
ExerciseSelf-Taught-Learning
- Soft-taught leaning是用的无监督学习来学习到特征提取的参数，然后用有监督学习来训练分类器.-Soft-taught leaning unsupervised learning is to learn the parameters of feature extraction, followed by supervised learning to train the classifier.
stacked-autoencoder
- 基于两层的层叠自编码的深度学习模型，前两层用于特征提取，再加一个Softmax分类器用于分类-Two stacked the depth of learning coding model based on the first two levels for feature extraction, coupled with a classifier for classifying Softmax
data
- 随机森林算法的构造过程：1、通过给定的原始数据，选出其中部分数据进行决策树的构造，数据选取是”有放回“的过程，我在这里用的是CART分类回归树。 2、随机森林构造完成之后，给定一组测试数据，使得每个分类器对其结果分类进行评估，最后取评估结果的众数最为最终结果-Random Forest algorithm construction process: 1, by a given raw data, which part of the decision tree data structu
DICLASS
- 各种不同的额分类器，带有交叉检验功能。并且含有最新的ELM函数-Different Classifier
mashijuli
- 模式分类之最小马氏距离分类器设计，对给出样本点进行分类处理-Minimum Mahalanobis distance classifier design pattern classification, the sample points are given for classification