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FASBIR
- Descr iption: FASBIR(Filtered Attribute Subspace based Bagging with Injected Randomness) is a variant of Bagging algorithm, whose purpose is to improve accuracy of local learners, such as kNN, through multi-model perturbing ensemble. Reference:
C45Rule-PANE
- Descr iption: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagn
论坛、商城、音乐、下载、二手市场、网址大全
- 集 论坛、商城、音乐、下载、二手市场、网址大全于一体，内附二十多种娱乐插件，多种风格，多种网站布局，所以娱乐插件与功能模块自由安装自由组合，给用户真真正正的DIY 风格如下：官方v1.5、官方v1.6、官方v2.0、文章系统专用、论坛风格-粉红、清雅淡绿、山中小屋、生活时尚、世纪情缘、古典、红与、深红格调、简洁普素、校园风格更多、校园风格 娱乐插件如下：赌大小、社区骞马场、论坛数据统计、普克牌 21点、美容中心、贺卡中心、流星许愿、flash游戏、签名档续费、
advanced_ensembel
- 神经网络集成的例子!基于南大周志华的论文，用神经网络集成解决异或问题!-neural network ensemble example! South dragon on the thesis, using neural network integration solutions differences or problems!
icsiboost-0.3.tar
- Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the
orensemble
- The program implements three large-margin thresholded ensemble algorithms for ordinal regression. It includes an improved RankBoost algorithm, the ORBoost-LR algorithm, and the ORBoost-All algorithm.
Transfer Learning with an Ensemble of Background Tasks
- boosting for transfer learning
基于贝叶斯网络的半监督聚类集成模型
- 已有的聚类集算法基本上都是非监督聚类集成算法,这样不能利用已知信息,使得聚类集成的准确性、鲁棒性和稳定性降低.把半监督学习和聚类集成结合起来,设计半监督聚类集成模型来克服这些缺点.主要工作包括:第一,设计了基于贝叶斯网络的半监督聚类集成(semi-supervised cluster ensemble,简称SCE)模型,并对模型用变分法进行了推理求解;第二,在此基础上,给出了EM(expectation maximization)框架下的具体算法;第三,从UCI(University of Ca
CSNN
- This package contains 6 algorithms for training cost-sensitive neural networks. They are over-sampling, under-sampling, threshold-moving, SMOTE and two ensemble methods, i.e. hard-ensemble and soft-ensemble.
coforest
- CoForest是一种半监督算法，处理集成学习及利用大量未标记数据得到更优越性能的假设。-CoForest is a semi-supervised algorithm, which exploits the power of ensemble learning and large amount of unlabeled data available to produce hypothesis with better performance.
61(Spectral-Clustering-Ensemble-Applied-to-SAR-im
- spectral clustering ensemble to SAR image segmentation.
K-means-Ensemble
- 该算法是基聚类算法为K-means，然后再进行聚类集成，方法为投票法-The algorithm is based on clustering algorithm for K-means, and then the clustering ensemble, method for voting
hi-ensemble-1.06
- 很好的集成学习代码，包括数据，适合初学者-Good ensemble learning code, including data, suitable for beginners
2--A-survey-of-clustering-ensemble-algorithms-(IJ
- 2- A survey of clustering ensemble algorithms (IJPRAI)
11---A-Survey-of-Cluster-Ensemble-10
- 11 - A Survey of Cluster Ensemble-10
7----Co-training-A-SEMI-SUPERVISED-ENSEMBLE-LEARN
- 7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6-7 - Co-training A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM-6
61---A-Genetic-Algorithm-Based-Ensemble-Approach-
- 61 - A Genetic Algorithm Based Ensemble Approach for Categorical Data Clustering.rar
17---Complementary-Ensemble-Clustering-of-biomedi
- 17 - Complementary Ensemble Clustering of biomedical data.rar
UAV-Motion-Planner-Ensemble
- MATLAB中无人机同步规划定位与制图的仿真(Simultaneous Planning Localization And Mapping For Unmanned Aerial Vehicles)
Improved Ensemble Empirical Mode Decomposition
- Improved Ensemble Empirical Mode Decomposition and its Applications to Gearbox Fault Signal Processing, Keywords: Complementary Ensemble Empirical Mode Decomposition(CEEMD), Improved Complementary Ensemble Empirical Mode Decomposition(ICEEMD), Gearbo