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machine-learning
- python3实现各种机器学习算法，包括knn算法，决策树算法，SVM算法，朴素贝叶斯算法等-Python3 realize all kinds of machine learning algorithms, including KNN algorithm, the decision tree algorithm, the SVM algorithm, naive bayesian algorithm, etc
C4.5
- 改进型的决策树算法，特别的实用，欢迎大家下载，也可以用到论文算法中-Improved decision tree algorithm, especially useful, welcome to download, you can also use paper algorithm
ID3
- 数据挖据决策树算法ID3算法java实现，包含引用文件，简单易懂-Data Mining Decision Tree Algorithm ID3, simple and easy to understand by java, contains references to files
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.
id3
- id3决策树算法，maxlen为数据维数，根绝数据自行修改，根据属性名修改main函数，可运行-id3 decision tree algorithms, maxlen for the data dimension, eradicate data modify, modify the main function according to the attribute name, you can run
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
CART
- CART是决策树算法的一种，是数据挖掘的重要组成部分。-CART is a decision tree algorithm, is an important part of data mining.
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.
Rtree
- R树是GUTTMAN于1984年提出的最早支持有序扩展的对象存取方法之一，也是目前应用最为广泛的一种空间索引结构，该资料为其的应用。-R tree is one of GUTTMAN first proposed in 1984 to support an orderly expansion of the Object Access Method, is currently the most widely used of a spatial index structure for the app
Decision-Tree-python
- python实现的决策树代码，包括数据，以及源代码- tree python code is implemented, including data, and source code
Decision-Tree-classifier15
- Decision Tree classifier by train and test
DecisionTree-sna
- Decision Tree by python programinig
project-1-skeleton
- 本压缩包内有决策树，knn，linear的方法（包括10-fold） 替换data可以直接使用。-You can find decision tree, inn and linear method in my zip, include 10-fold. The data.py can replaced by yourself
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
DecisionTreeAndRDF-master
- id3决策树算法和随机森林算法，讲的很清晰，步骤很详细-id3 decision tree algorithms and random forest algorithms, said very clearly, very detailed step
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.
CARTandRFclass
- 使用Decision Tree 实现cart和实现随机森林算法，比较好的学习工具，而且也能用，速度之前和别人讨论，被优化过-using decision tree trick to fullfil the CART and RandomForest ,it is good learing tool ,and ,practical use. it was optimize speed
decision-making-tree
- 决策树的Python代码实现，要所报内含原数据-Decision Tree Python code, containing the original data to be reported
Cart-tree
- 实现CART树回归，树的生成与剪枝过程，并与简单线性回归进行对比-Implement a regression tree generation algorithm when the leaf nodes indicate 3rd order polynomials. Test your program with the dataset and compare the results with those of simple linear regression
sklearn-tree-BN-knn
- 分类器的性能比较与调优: 使用scikit-learn 包中的tree，贝叶斯，knn，对数据进行模型训练，尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较，分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the dat