搜索资源列表
adaboostPknnPlbp
- adaboost+knn+lbp 人脸识别代码 经典算法-adaboost+knn+lbp face recognition code classical algorithm
10Algorithms-08
- This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms
10Algorithms-08
- This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms
10-da--suanfa
- 讲述了最著名的十大数据挖掘算法，经典资料，国际权威的学术组织the IEEE International Conference on Data Mining (ICDM) 2006年12月评选出了数据挖掘领域的十大经典算法：C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART.-About the top ten most famous data mining algorithms, the
dataming
- 介绍数据挖掘的10种主要算法及其应用 一种透过数理模式来分析企业内储存的大量资料，以找出不同的客户或市场划分，分析出消费者喜好和行为的方法。 -Top 10 algorithms in data mining his paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006:
MachineLearning
- 机器学习的十大算法，AdaBoost，Apriori，CART，EM，K-means，kNN，PageRank，SVM-Ten machine learning algorithms, AdaBoost, Apriori, CART, EM, K-means, kNN, PageRank, SVM
spider20060724
- 机器学习和模式识别工具包spider。内容很丰富。包含svm 决策树（C45,J48）、svm、knn、adaboost、bagging、hmm（隐马尔科夫模型）、随机树（random forest）等-Machine learning and pattern recognition toolkit spider. Very rich in contents. Tree contains svm (C45, J48), svm, knn, adaboost, bagging, hmm (hidd
Pattern_Recognition
- 自己在硕士期间用到的各种模式识别，机器学习，数据挖掘算法的matlab程序。C4_5,NN，SVM，adaboost,KNN等-During their Master used a variety of pattern recognition, machine learning, data mining algorithm matlab program. C4_5, NN, SVM, adaboost, KNN, etc.
Adaboost
- 网上看到的matlab做adaboost的小例子，正在学习中(matlab for learning adaboost-knn)
weka机器学习十大算法
- 对机器学习领域的十个经典算法进行了详细介绍，包括：AdaBoost、Apriori、C4.5、CART、EM、K-means、kNN、PageRand、SVM和朴素贝叶斯(Ten classical algorithms in machine learning domain are introduced in detail, including AdaBoost, Apriori, C4.5, CART, EM, K-means, kNN, PageRand, SVM and Nave Baye
classical-machine-learning-algorithm-master
- bayesian, k-means, knn, SVM, The Apriori algorithm, expectation-maximization(EM), C4.5, page rank, AdaBoost, CART
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.)