YiFraternity / OS-K-Means
现有聚类算法面向高维稀疏数据多未考虑类簇可重叠和离群点的存在，导致聚类效果不理想。针对此，提出一种可重叠子空间K-Means聚类算法(An Overlapping Subspace K-Means Clustering Algorithm, OS-K-Means)。给出类簇子空间计算策略，在聚类过程中动态更新每个类簇的属性子空间，并定义合理的约束函数指导聚类过程，从而实现类簇的可重叠性与寻找离群点的效果。具体地，定义合理的目标函数对传统的K-Means算法进行修正，利用熵权约束分别计算每个类簇中每个维度的权重，使用权重值来标识对不同类簇中维度的相对重要性，并加入对重叠程度和离群值数量控制的参数。
☆30Updated 5 years ago
Alternatives and similar repositories for OS-K-Means:
Users that are interested in OS-K-Means are comparing it to the libraries listed below
- 数据预处理之缺失值处理，特征选择☆21Updated 5 years ago
- Optimizing k-means++ initialization using PSO☆17Updated 8 years ago
- 由时间空间成对组成的轨迹序列，通过循环神经网络lstm，自编码器auto-encode，时空密度聚类st-dbscan做异常检测☆70Updated 5 years ago
- This is an implementation of the paper on "Improved K-means algorithm based on density Canopy".☆31Updated 5 years ago
- 常用的特征选择方法☆68Updated 2 years ago
- Affinity Propagation Clustering with DTW distance on temporal sequence classification☆19Updated 6 years ago
- AutoEncoder implements by keras. Including AE, DAE, DAE_CNN, VAE, VAE_CNN, CVAE, Sparse AE, Stacked DAE.☆41Updated 4 years ago
- 使用 tensorflow2.0 实现图卷积神经网络GCN☆20Updated 4 years ago
- 改进的k-prototypes聚类算法☆18Updated 4 years ago
- 聚类算法k-means的简单实现☆37Updated 6 years ago
- 机器学习的特征工程，包括特征抽取、特征预处理、特征选择、特征降维。☆25Updated 5 years ago
- 本项目开发了一个机器学习和深度学习的训练工具。该训练工具基于sklearn和pytorch，不仅支持常规训练、交叉验证训练，还支持贝叶斯搜索参数，并可随时自动保存训练模型和日志。☆11Updated last year
- Removal of information from co-association matrix for clustering ensemble☆17Updated 5 years ago
- Oversampling method based on relative density☆11Updated 4 years ago
- Source code of our paper: An overlapping community detection algorithm based on density peaks☆13Updated 6 years ago
- 基于遗传算法的特征选择☆127Updated 5 years ago
- Code for *Unsupervised Anomaly Detection for Intricate KPIs via Adversarial Training of VAE*☆24Updated 5 years ago
- 使用AR自回归模型与长短时记忆网络进行时间序列数据预测☆18Updated 4 years ago
- Implementation of iForest Algorithm for Anomaly Detection from scratch☆27Updated 5 years ago
- 时间序列异常检测☆52Updated 5 years ago
- 支持向量机(SVM)——分类预测，包括多分类问题，核函数调参，不平衡数据问题，特征降维，网格搜索，管道机制，学习曲线，混淆矩阵，AUC曲线等☆52Updated 7 years ago
- 基于Python实现了K-Means、GMM、DBSCAN、AGNES等四种常见的聚类算法☆68Updated 5 years ago
- 基于KNN聚类算法结合Dynamic Time Warping（动态时间调整）的时间序列分类☆58Updated 5 years ago
- 标签传播算法☆11Updated 6 years ago
- Solution in KDD Cup2021 Multi-dataset Time Series Anomaly Detection Competition☆10Updated 3 years ago
- K-Means聚类算法及其改进☆31Updated 6 years ago
- This algorithm is based on the paper 'K-Means clustering algorithm Based on Adapative Feature Weighted'☆28Updated 5 years ago
- Time Series Prediction, Stateful LSTM; 时间序列预测，洗发水销量/股票走势预测，有状态循环神经网络☆56Updated 7 years ago
- Stacked Denoising AutoEncoder☆76Updated 5 years ago