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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
DataDemo
- this a data for a small application. the aim of this work is to active my account, tks :D-this is a data for a small application. the aim of this work is to active my account, tks :D
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
my-k-means
- 这是一个k-means聚类算法,将一个四维量(比如有明确物理意义的花瓣长宽花萼长宽)按照几个中心点分成几类-This is a k-means clustering algorithm, a four-dimensional volume (such as a clear physical meaning petals calyx length and width aspect) is divided into several categories according to several ce
FCM-(2)
- 本人自己写的模糊均值算法,采用c#语言,经过测试可以运行。-I write my own fuzzy average algorithm, using c# language, through the test can be run.
LDA-topic-model
- 首先声明,这是别人写的LDA主题模型代码,本人测试过,可以运行,但是输出跟输出有点不尽人意,输入的是词的序号和该词在文档中出现的次数,要是可以直接读取文档就完美了。输出是主题以及词在该主题出现的概率,其中得到的主题我就看不懂了,不知道是算法问题,还是因为我的水平有限。在研究LDA主题模型的朋友,可以下载试一下-First statement, which is written by someone else LDA topic model code, I tested, you can run,
DPCxy
- Science上发表的Clustering by fast search and find of density peaks,该代码为我改编后的matlab密度峰聚类算法代码-Science Clustering published on the by fast search and find of density peaks, the code for my adaptation of the MATLAB density peak clustering algorithm code
node2vec-master-python3
- 斯坦福大学的node2vec模型,做图嵌入的,说明很详细分享一下,,原文件是Python2做的,我改的Python3的,分享一下(The node2vec model of Stanford University is embedded in the diagram, and the descr iption is shared in detail. The original file is made by Python 2, and my modified version of Python
