搜索资源列表
svmcls
- 李荣陆老师做的文本分类器,特征选择方式包括全局和按类别选取，概率估算方法支持基于文档（布尔）统计和基于词频统计，支持三种特征加权方式，特征评估函数包括信息增益、互信息、期望交叉熵、X^2统计，文本证据权重，右半信息增益，分类方法包括支持向量机SVM和K近邻KNN，(text classifier that was written by Li Ronglu)
kmediod
- k-mediod、knn、uci数据集。 数据挖掘、机器学习中的经典聚类、分类算法(K-mediod, KNN, and UCI data sets. Data mining and classical clustering and classification algorithms in machine learning)
MachineLearning-master
- 机器学习算法，包括knn等，K最近邻(kNN，k-NearestNeighbor)分类算法是数据挖掘分类技术中最简单的方法之一。(machine learning algorithm)
BreastCancer
- Java实现机器学习经典分类算法，代码中实现了决策树、贝叶斯和KNN三个分类算法(Java implements the classic classification algorithm for machine learning. The code implements three classification algorithms: decision tree, Bayes and KNN)
classifier
- 一些分类器尝试，包括SVM，KNN，自带树与adaboost或者bagging结合等。(Some classifiers test,such as SVM,KNN,etc, including test data. Only some of the methods are included in the main.m.)
机器学习算法matlab实现
- KMeans、EM、KNN等分类和聚类算法
115157718fruitvegtablerecognition_knn
- 基于KNN算法对多种水果和蔬菜图像进行分类识别，识别率较高(Based on KNN algorithm, a variety of fruit and vegetable images are classified and recognized with high recognition rate)