搜索资源列表
AdaBoost
- 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 training set for training different classifiers (weak classifiers), then these weak classifiers together to f
NaiveBayes
- 贝叶斯分类器，机器学习十大经典算法之一，基本的实现-Naive Bayes
AdaBoost
- 加强树算法的一个实例，最后取得了很好的分类结果，便于推广，分类器的代码可以根据实际进行更改。-Strengthen an instance tree algorithm, finally achieved good classification results, easy to promote, classification code can actually make changes.
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.
knn
- KNN分类器的MATLAB代码，速度快效果好，适合初学者使用。-KNN search without using any gancy data structure, such as kd-tree. However, it is the fastest knn matlab implementation I ever found.
fisher
- 利用matlab实现Fisher分类器，可以对线性可分的样本进行线性分类-Fisher classification algorithm using matlab realize, you can sample linearly separable linear classification
emial-spam
- 基于感知器算法的垃圾邮件识别，先通过训练集训练出分类器，然后通过测试集验证-Perceptron based spam detection algorithm
DecisionTree
- matlab代码实现决策树，是学习数据挖掘的基本分类器的入门代码-DecisionTree classifier about data mining coded by matlab
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
minimum_spanning_tree
- 本程序是基于最小洗漱树的分类器 可得到分类效果不错的分类器-This procedure is based on a minimum wash tree classifier good classification results obtained classifier
SgdClassifier
- 随机梯度下降分类器。本实验的实验平台为eclipse，只需导入(import)即可运行。输出方式为控制台输出，能够提供的评价数据有test error, percision, recall以及F1-measure。-Stochastic gradient descent classifier. In this study, experimental platform for eclipse, just import (import) to run. Output of the console o
RandomForestaAdaBoost
- 随机森林，决策树以及adaboost分类器的java实现。随机森林和adaboost都基于决策树完成。-Random forests, tree and adaboost classifier java. Random Forest and adaboost are based on the decision tree is complete.
KNN
- K-最邻近分类器的一个实例，实现了对数据的分类，内含测试数据-an example of K-nearest algorithm,containing a set of test data
test1
- scikit-learn常用分类器的实例-Examples of commonly used scikit-learn classifier
CuCao2ClassTrain
- 基于粗糙集的分类规则提取和分类规则约简。首先进行粗糙分类器训练，然后将复杂的分类规则降维成简单的分类规则，但分类精度不变。-Rough classification learning rules are trained and extracted based on rough sets and complex classification rules are dimensionally reduced into simple classification rules, but the class
ensemble_2.0
- 集成分类器，用于软判决。 常用于图像隐写和隐写分析。-Integrated classifier for soft decision.
algorithm
- 多线性SVM分类器，在实现分类的同时，能很好的聚类-Multi-linear SVM classifier to classify the same time, can be a good clustering
svm
- 最经典的机器学习方法svm分类器的python实现-The most classic machine learning svm classifier python realization
贝叶斯
- 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(The classification principle of Bias classifier is to calculate the posterior probability by using Bias's formula through the prior probability of an object, that is, the proba