搜索资源列表
KNN
- 数据挖掘导论中的K近邻聚类算法,用C++编写而成。-Introduction to Data Mining of the K neighbors clustering algorithm, using C++ has been prepared by.
www
- 一本将基于近邻传播算法的半监督聚类的算方法书.对于聚类研究的很有帮助-Abstract: A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP is an efficient a
DM_YeDan
- KNN(K最近邻)分类算法以及K-means(K均值)聚类算法是应用广泛的两种算法。本代码是在VS2010环境下,用 C++语言在基于KNN及K-means算法下,实现了对Iris数据集的分类与聚类。-KNN (K nearest neighbor) classification algorithm, as well as K-means (K mean) clustering algorithm is widely used two algorithms. The code VS2010 en
KNNpython
- python实现的k-近邻算法,用于数据分类。机器学习实战-k- nearest neighbor python implemented for data classification. Machine learning combat
kNN
- 使用k-近邻算法改进约会网站的配对算法和使用k-近邻算法的手写数字识别系统-Use k- nearest neighbor matching algorithm to improve the dating sites and use of k- nearest neighbor handwritten numeral recognition system
mechine-learning
- 本书第一部分主要介绍机器学习基础,以及如何利用算法进行分类,并逐步介绍了多种经典的监督学习算法,如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树(CART)算法等。第三部分则重点介绍无监督学习及其一些主要算法:k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。 全书通过精心编排的实例,切入日常工作任务,摒弃学术化语言,利用高效的可复用Python代码来阐释如何处理统