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
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
released
- 本文件是我自己写的决策树的一个例子，很适合初学者学习，用决策树分类，实现很简单-This document is an example of the decision tree of my own writing, it is suitable for beginners to learn, decision tree classification, to achieve a very simple
machine-learning
- 一些关于机器学习初学者可能会遇到的代码训练。分类学习等的代码分享。-some machine learning problems.
perception
- 用R语言进行机器学习中关于简单分类以及perception分类的代码。-some code about the easy classify and perception training in machine learning, using R.
ClassicalELM
- 通过极限学习机的相关算法，实现数据的预测、回归、分类，从而有利益数据的处理-Processed through the relevant algorithm ELM achieve prediction data, regression, classification, and thus interest data
svm
- svm 分类算法 java源代码 很好的学习程序-svm classification algorithm java source code is a good learning program
NaiveBayes-master
- 对文本信息进行分类，训练和学习，利用朴素贝叶斯算法实现。-Text information on the classification, training and learning, with Naive Bayes 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
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
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
knn
- 最简单的机器学习分类方法knn算法的python实现-The easiest method of machine learning classification algorithm python achieve knn
ex2-003(Week3)_finished
- 百度NG的机器学习教程 文档以及程序代码，对于初学者很有帮助，有助于理解分类聚类等基本的机器学习算法， week_3-Baidu NG machine learning tutorial documentation and program code, useful for beginners, help to understand the classification clustering week3
ex3-003(Week4)_finished
- week4 百度大牛NG的机器学习教程 文档以及程序代码，对于初学者很有帮助，有助于理解分类聚类等基本的机器学习方法-week4 Baidu Daniel NG machine learning tutorial documentation and program code, useful for beginners, help to understand the basic classification clustering of machine learning methods
ex4-003(Week5)_finished
- week5 百度大数据实验室NG的机器学习教程，包括文档以及代码，有些基本的分类聚类的机器学习算法，很有帮助-week5 Baidu large data laboratory NG machine learning tutorials, including documentation and code, some basic classification machine learning clustering algorithm helpful
ex5-003(Week6)_finished
- week6 百度大数据实验室NG的机器学习教程，包括文档以及代码，有些基本的分类聚类的机器学习算法，对于初学者很有帮助-week6 Baidu large data laboratory NG machine learning tutorials, including documentation and code, some basic clustering classification machine learning algorithms, very helpful for beginne
文本深度挖掘
- 用于分析文档，分析情感指数，正负面情绪，及新闻分类(Used to analyze documents, analyze sentiment, positive and negative emotions, and classify news)
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)
专利文本分类
- 对大量的专利文本文件进行处理，然后利用机器学习的算法进行挖掘，实现对专利的分类(A large number of patent text files are processed, and then machine learning algorithm is used for mining.)
Decision_tree-python
- 使用决策树（包括ID3,C45,CART）对数据做多分类预测。(Use Decision Tree to classify.)