搜索资源列表
SVM
- 在机器学习领域，支持向量机SVM(Support Vector Machine）是一个有监督的学习模型，通常用来进行模式识别、分类、以及回归分析。-In the field of machine learning, support vector machine SVM (Support Vector Machine) is a supervised learning model, typically used for pattern recognition, classification, an
Linear-classifier
- 本资源用matlab代码实现了模式识别的线性分类器，对于线性可分的模式能够正确分类。-The resources used matlab code to achieve a pattern recognition linear classifier, for linearly separable model can correctly classified.
k-means-cluster
- 分类算法中k均值分类算法，可以用于简单的模式识别中去。-Classification algorithm of k-means classification algorithm, which can be used in a simple pattern recognition.
pattern-identification
- 主成分分析、Fisher判别法与支持向量机在模式识别中的应用-Application of principal component analysis, Fisher discriminant analysis and support vector machine in pattern recognition
machine-learning-(2)
- 模式识别和机器学习，数据挖掘方向的专业性程序代码-Pattern recognition and machine learning, data mining direction of the professional code
data--mining
- 模式识别和机器学习，数据挖掘方向的专业性程序代码-Pattern recognition and machine learning, data mining direction of the professional code
ml
- 模式识别和机器学习，数据挖掘方向的专业性程序代码-Pattern recognition and machine learning, data mining direction of the professional code
ml2
- 模式识别和机器学习，数据挖掘方向的专业性程序代码-Pattern recognition and machine learning, data mining direction of the professional code
classifier
- 一种分类算法工具箱，可以进行人脸识别，对模式识别和分类算法很有用-A classification algorithm toolbox, face recognition, pattern recognition and classification algorithms useful
PCA-AND-PNN
- 应用主成分分析对数据降维，将得到的数据用于概率神经网络训练，进行模式识别。对于一组新数据，先计算主成分得分，再输入训练好的概率神经网络，就会得到识别结果，即改组数据属于何种类别。-Principal component analysis of the data reduction, data will be obtained for the probabilistic neural network training, pattern recognition. For a new set of d
Bayesian-networks-for-Data-Mining
- 贝叶斯网络的介绍及其在数据挖掘和模式识别中的应用-Introduction Bayesian network and its application in data mining and pattern recognition
knn_demo
- 可以demo的KNN分类器，对模式识别十分重要的作用，有着较好的分类效果，可以帮助新手更好的理解KNN原理，对人脸识别有着很好的演示作用。-Can demo KNN classifier, the pattern recognition is an important role, has a good classification effect, can help beginners a better understanding of KNN principle, has a very good
distanceKNN
- 可以分别设置度量距离的KNN分类器，有欧式和马氏距离。对模式识别十分重要的作用，有着较好的分类效果，可以帮助新手更好的理解KNN原理，对人脸识别有着很好的演示作用。-Distance can be set respectively KNN classifier, style and markov distance. For pattern recognition is an important role, has a good classification effect, can help be
Kmeans
- 按照模式识别一书，实现k均值聚类的matlab版本代码-According to the book Pattern Recognition , implement k-means clustering matlab version of the code
cfmatrix
- 这是混淆矩阵源代码，可以输出分类结果的混淆矩阵，用于模式识别，数据挖掘等。-this is cfmatrix code
apcluster
- 聚类算法是应用于数据挖掘和模式识别中很重要的一种分析方法，ap是新提出的一种聚类算法，不需要事先指定聚合点的数目-Affinity Propagation (AP) clustering has been successfully used in a lot of clustering problems. However, most of the applications deal with static data.
55e9ae658d29
- 基于bagging算法的C++程序，包括matlab程序的结合。代码简单易懂，适合模式识别的初学者。-Based bagging algorithm C++ procedures, including combining matlab program. Code is easy to understand for beginners pattern recognition.
svm_python
- 在机器学习领域，支持向量机SVM(Support Vector Machine)是一个有监督的学习模型，通常用来进行模式识别、分类、以及回归分析。本程序是SVM的python实现，用的是SMO算法。只能进行分类，并且能够显示图形结果。-In the field of machine learning, support vector machines SVM (Support Vector Machine) is a supervised learning model is usually use
myKmeans.m
- 模式识别学习中使用matlab编写的Kmeans算法实现的小程序-Learning to use pattern recognition matlab prepared Kmeans algorithm small program
knn
- 模式识别中的k近邻算法，经过测试，运行结果很好。 最小距离分类器 : 它将各类训练样本划分成若干子类，并在 每个子类中确定代表点 。测试样本的类别则以其与这些代表点距离最近作决策。该方法的缺点是所选择的代表点并不一定能很好地代表各类，其后果将使错误率增加。(The k nearest neighbor algorithm in pattern recognition has been tested and the result is very good. Minimum distance c