搜索资源列表
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.
SVM_Finger
- 指纹图像的质量测量与评价,在指纹图像分割、增强及指纹匹配等环节都有重要应用. 同时,指纹图像的质量分类,对指纹识别算法的适用性研究也有重要意义. 本文提出一种基于支持向量机的指纹图像质量分类方法.该方法选择梯度、Gabor特征、方向对比度等指标,利用支持向量机有效实现指纹图像质量分类. 并采用少类样本合成过采样技术( SMOTE)降低指纹图像质量好坏的类别不平衡问题对分类的影响. 理论分析和实验结果都表明该方法能够较为有效地提高指纹图像
CSNN
- 这个包包含6个代价敏感神经网络训练算法。-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-e
SMOTE
- matlab的smote算法，可以用于分类时样本数据不平衡的问题-matlab smote algorithm, can be used to sample data classification problem of unbalanced
SMOTEBoost
- 分类非平衡数据的SMOTEboost算法-This code implements SMOTEBoost. SMOTEBoost is an algorithm to handle class imbalance problem in data with discrete class labels. It uses a combination of SMOTE and the standard boosting proced
pattern-recogniton
- 对类别不平衡的分类问题的几种算法实现，包括PNN，smote，BP-AdaBoost-Several algorithms for class imbalance classification problem ,including PNN, smote and BP-AdaBoost
ADASYN_upd2
- Modfied version of SMOTE
SMOTE
- SMOTE algorithm code
SMOTE
- 本工具为不平衡数据分类领域重要的过采样算法SMOTE.-This tool is an important field of unbalanced data classification oversampling algorithm SMOTE.
SMOTE
- The SMOTE function takes the feature vectors with dimension(r,n) and the target class with dimension(r,1) as the input. And returns final_features vectors with dimension(r ,n) and the target class with dimension(r ,1)
smote
- 随着数据的大量出现，非平衡问题显得尤为突出，该算法能很好的解决非平衡分类问题(imbanlanced classification)
SMOTE
- Python语言实现针对不平衡分类的SMOTE升采样算法，并通过SVM实现分类(We implements the SMOTE over-sampling algorithm via Python language for unbalanced classification, and achieves the classification of Glass data through SVM algorithm.)
1-data processing.R
- 数据预处理,对于分类前的文件进行预处理。查看数据的类型。进行smote(data pre-processing.For pre-classification documents pretreatment. Check the type of data. and using smote to Solve the problem of data imbalance)
SMOTE
- smote算法，在matlab下的实现，以function的形式，可直接调用(The smote algorithm, implemented under Matlab, can be called directly in the form of function)
SMOTE
- 通过合成小类样本，使小类的样本数与大类的样本数相同，这样类不平衡的问题就解决了，在小类上的分类准确率提高(By synthesizing small class samples, the sample number of the small class is the same as the number of the large class, so the problem of unbalance is solved, and the
SMOTE
- SMOTE过采样算法的matlab代码，，，(SMOTE algorithm on matlab platform)
SMOTE
- 针对非平衡数据集中少数类数据过少的问题进行过采样，SMOTE算法采用人工合成稀有类的方法将非平衡数据变为平衡数据之后在用于数据挖掘(Over sampling techniques for minority data)
Random_Forest
- 内涵PCA降维;SMOTE插值;t-SNE降维等算法的随机森林算法，以及鸢尾花数据集，有利于新手或者工程性实验借鉴~(Connotative PCA dimensionality reduction; SMOTE interpolation; t-SNE dimensionality reduction algorithms such as random forest algorithm, as well as iris data se
MATLAB_SMOTE
- SMOTE插值算法，补全数据的不平衡性。(SMOTE interpolation algorithm to complete the imbalance of data.)
smote
- smote过采样方法对不平衡数据集进行人工数据合成(smote oversampling and classification)