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PSO
- 该文件为粒子群算法优化支持向量机模型参数的matlab代码 支持向量机模型为专门用于处理不平衡数据的成本控制型支持向量机模型-Matlab code of the file support vector machine model parameters for particle swarm optimization support vector machine model for cost control, support vector
PMF
- Probabilistic Matrix Factorization 算法 用VS2010 C++实现，用于协同过滤。performs well on the large, sparse, and very imbalanced Netflix dataset。-we present the Probabilistic Matrix Factorization (PMF) model which scales linearly
ELM_kernel
- 基于极限学习机的不平衡数据集分类，性能极好，且速度较快-Based on extreme learning machine for imbalanced data sets classification, excellent performance, and faster
svd
- 用于协同过滤推荐算法，svd矩阵分解算法 C++实现-Matrix Factorization , performs well on the large, sparse, and very imbalanced Netflix dataset
Weighted-ELM-Codes-for-Binary-Problems
- Weighted ELM for imbalanced datasets - Weighted-ELM W. Zong, G.-B. Huang, and Y. Chen, “Weighted extreme learning machine for imbalance learning,” Neurocomputing, vol. 101, pp. 229-242, 2013.
E-Algorithm
- E-Algorithm,适用于不平衡数据的分类，而不用对数据进行预处理。MATLAB-the algorithm is suited for the classification of imbalanced data
CAIE_accompanying-code
- 加权支持向量机的控制图模式识别方法，不平衡的分类异常控制模式与支持向量机的趋势 -A weighted support vector machine method for control chart pattern recognition imbalanced classification of abnormal control trend patterns with SVM
literature-review
- boosted svm for classification of imbalanced data
paper7
- On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets
IJETT-V2I3P204
- Design of Shunt Active Power Filter to eliminate the harmonic currents and to compensate the reactive power under distorted and or imbalanced source voltages in steady state
ImageClassification-master
- 在这个项目中，我们的目标是建立一个识别和大小231x231图像呈现对象分类系统。我们得到了一组训练图像，每四个标签之一：1飞机；汽车2；3马，否则。我们提供了两个特点：一是方向梯度直方图（HOG），其尺寸为5408；另一个是overfeat ImageNet美国有线电视新闻网的特点，其尺寸37000。关于测试图像，我们只给出了每个图像的功能，没有标签，结果判断由平地机。我们的目标是提供二进制和多个预测。平衡错误率（BER）是我们的性能评
imbalanced-learn-master
- 基于不均衡数据的学习，包含各种机器学习算法，python 操作(imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance. It is compatible with scikit-learn_ and