搜索资源列表
Ap
- 数据挖掘中关联规则挖掘算法-apriori，的Python实现，代码中有测试样本-Data mining association rule mining algorithm-apriori, implementation of Python code in a test sample
FPtree
- 数据挖掘中关联规则算法的FPtree算法的Python实现。FPtree算法比apriori算法更擅于处理大规模的数据-Data Mining Association Rules algorithm FPtree algorithm implemented in Python. FPtree algorithm apriori algorithm is more than adept at handling large data
dbscan_
- 数据挖掘中DBSCAN聚类算法的实现，用python语言实现，亲测可用。-The realization of DBSCAN clustering algorithm in data mining, using Python language to achieve, pro test available.
KNN-implement-by-python
- 该程序是用python编写一个K近邻算法，通过该例子可以掌握K近邻算法，是学习数据挖掘的一个高效的算法。-The program is written in python a K-nearest neighbor algorithm, this example can grasp the K-nearest neighbor algorithm, a learning data mining and efficient algorithms.
plot_svm_anova
- plot_svm_anova机器学习中大数据挖掘python文件-Machine learning cuhk python file data mining
LDA
- python数据分析与数据挖掘 chapter15-python data analysis and data mining chapter15
hierarchical_clustering
- python数据挖掘hierarchical_clustering-python data mining hierarchical_clustering
chapter11code
- python 数据挖掘 chapter-python data mining chapter11
learning-data-mining-with-python
- 《python数据挖掘入门与实践》随书源代码，Chapter1-Chapter12.使用ipython notebook运行，包括社会媒体挖掘，作者归属，新闻语料分析，大数据处理等应用实例。-Python data mining entry and practice with the book source code, using Chapter1-Chapter12. IPython notebook operation, including social media mining, aut
time-sequence
- 数据挖掘，时间序列分析算法的实现和应用，python语言开发-data miniing
Cluster
- 机器学习和数据挖掘中常用的K-means聚类算法，包含两个文件，kmeans.py是Python实现代码，bank-data.csv是测试数据-Machine learning and data mining commonly used K-means clustering algorithm contains two files, kmeans.py is a Python implementation code, bank-data.csv test data
Data-mining
- 5种Python数据挖掘算法：Bayes,Apriori,K-means,ID3,K-data mining of Python
Python for network worm
- 基于selenium的网络爬虫，主要是从网站爬取数据信息用来进行分析和挖掘潜在的商业价值(Internet worm based on selenium)
hearder.py
- 利用python抽取单个电影的豆瓣影评信息(use python to get all user reviews from douban movie site)
利用Python进行数据分析
- 数据挖掘python语言的学习资料，包括常用算法的实现和工具的使用(Data Mining Pthon Language Learning Materials, including the Implementation of Common Algorithms and the Use of Tools)
数据挖掘各类算法
- apriori、id3、c4.5、fp树等算法的的python实现(Python implementation of apriori, id3, c4.5, FP Tree and other algorithms)
共享单车数据挖掘Python源码
- 关于使用Python进行共享单车数据挖掘，数据分析源码，包括数据清洗，可视化等
Python数据分析与挖掘实战
- 本书共15章，分两个部分：基础篇、实战篇。基础篇介绍了数据挖掘的基本原理，实战篇介绍了一个个真实案例，通过对案例深入浅出的剖析，使读者在不知不觉中通过案例实践获得数据挖掘项目经验，同时快速领悟看似难懂的数据挖掘理论。读者在阅读过程中，应充分利用随书配套的案例建模数据，借助相关的数据挖掘建模工具，通过上机实验，以快速理解相关知识与理论。(There are 15 chapters in this book, which are divided into two parts: the basic c