搜索资源列表
fcm_py
- fcm聚类算法的python实现。输出类内平均距离类间平均距离。-FCM clustering algorithm python realized. Output class average distance between class in the average distance.
Source-Code
- 数据挖掘经典算法实现。使用这个算法分别对图片和DBLP上面学者的合作关系图进行了聚类，然后评估聚类的结果。算法实现用的java，DBLP的数据的搜集和预处理是用Python编写。-Classical data mining algorithm. Using this algorithm, respectively, pictures and cooperation between scholars DBLP above graph clustering, and then evaluate th
canopy
- 一种新的聚类方法，结合k-means，用Python作为开发工具-a kind of clustering
cluster
- python语言实现k-means算法和Fast Search And Find Of Density Peaks算法用于文本聚类，-python language implements k-means algorithm and Fast Search And Find Of Density Peaks for text clustering algorithm,
python-code-for-Machine-learning
- 用于机器学习的全方位python代码，包括K-近邻算法、决策树、朴素贝叶斯、Logistic 回归 、支持向量机、利用 AdaBoost 元算法提高分类性能、预测数值型数据：回归、树回归、利用 K-均值聚类算法对未标注数据分组、使用 Apriori 算法进行关联分析、使用 FP-growth 算法来高效分析频繁项集、利用 PCA 来简化数据、利用 SVD 简化数据、大数据与 MapReduce-The full range of python code for machine learning
recommender-master
- 基于多种算法的推荐系统python实现，其中包括了SVD、聚类分析等多种热门算法，并且有很强的可扩展性(A recommender system based on several kinds of algorithms, written in python)
g13tsr
- 机器学习启蒙实战学习源码，回归模型，分类模型，聚类和相似度模型，推荐系统，深度学习等学习代码。(Machine learning, practical combat learning source,regression model, classification model, clustering and similarity model, recommendation system, depth learning and other learning code.)
python-graph-clustering-master
- 蛋白质相互作用网络中，蛋白质复合物的预测，内含有多有经典的聚类算法(predict protein complex from PPI network)
Kmeans
- 用Python语言实现的大规模数据聚类，附实验报告(Large-scale data clustering with Python language, with experimental reports)
kmeans
- 对数据和图像进行聚类分析，k-means聚类方法多应用于模式识别，人工智能，机器学习等方面(Clustering analysis of data and images, K-means clustering method should be used in pattern recognition, artificial intelligence, machine learning and so on)
kmeans
- 使用python编写kmeans聚类的例程，含画图(use python to implement kmeans algorithm)
模式识别 聚类
- 模式识别作业，两种聚类算法kmeans,dbscan，python算法(pattern recognition homework)
K-means&DBSCAN
- python实现K-means聚类算法和DBSCAN算法，都是最简单的聚类(Python implements k-means clustering algorithm and DBSCAN algorithm, which are the simplest clustering)
Kmeans
- python语言实现kmeans聚类，机器学习算法(Kmeans clustering in Python language)
kmean
- 一个学习k均值聚类的实例，代码实现了其基本原理，简单易懂，带有测试，训练数据集，可直接上手操作(A learning k-means clustering example, the code to achieve its basic principles, easy to understand, with a test, training data set can be used directly)
kMeans
- 用python实现k-means算法。随机生成二位可视化数据集 然后进行可视化聚类(The k-means algorithm is implemented with Python. Randomly generate two bit visual data set and visualize clustering.)
DENCLUE2.0 algorithm for python
- DASCAN 聚类算法例程，实现平面内点的分类(Clustering algorithm routines)
Lecture 12
- DBSCAN 聚类 skit-learn(DBSCAN cluster skit-learn)
k-means
- k-means算法实现的数据分类，python代码，可直接运行(K-means algorithm to achieve data classification, Python code, can be run directly)
聚类算法的课件和编程源码
- 聚类算法的课件和基于Python的编程源码，聚类有很多方法，这里列举了常见的几种，并附上基于Python的代码