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[
Documents
]
基于主成份分析的Bagging集成学习方法
DL : 0
机器学习中数据集的冗余特征会影响学习器的泛化能力,一些流行方法如支持向量机和集成学习也难免于 此.研究了利用主成份分析进行特征变换对Bagging集成学习算法的影响,提出一种称为PCA—Bagging的算法,并与 其它算法比如单个支持向量机、支持向量机Bagging集成、带有特征变换的单个支持向量机等进行了性能比较.在 多个UCI标准数据集上的实验表明PCA—Bagging算法具有更好的性能,这说明即使是泛化能力很强的集成学习方 法其学习的数据也需要进行适当的特征变换
Date
: 2011-04-26
Size
: 223.3kb
User
:
zero_m
[
Graph program
]
PCA
DL : 0
对UCI数据集之一进行PCA特征抽取实验,给出在二维PCA特征空间的数据散点图。-UCI data sets on one of PCA feature extraction experiments are given in the two-dimensional PCA feature space of the data scatter.
Date
: 2025-07-09
Size
: 1kb
User
:
chris
[
Special Effects
]
PCAforUCI
DL : 0
对UCI数据集做PCA图像特征提实验,PCA是一种很重要的方法-PCA on the UCI data sets to do the image feature extraction experiment, PCA is a very important method
Date
: 2025-07-09
Size
: 1kb
User
:
chen
[
matlab
]
wine
DL : 1
pca-kmeans聚类 先将数据(wine,uci数据集)降维处理,在进行聚类-pca-kmeans clustering use the data of uci:wine.
Date
: 2025-07-09
Size
: 7kb
User
:
王
[
matlab
]
PCA
DL : 0
PCA算法实现对数据降维,train_sample为训练样本,train_class为训练样本的分类结果,test_sample为测试样本,test_class为测试样本的分类结果,可以从UCI下载数据集进行调用~-PCA algorithm for data dimensionality reduction, train_sample of training samples, train_class for the classification of training samples, test_sample of test samples, test_class for the classification results of the test samples can be called from UCI download data sets ~
Date
: 2025-07-09
Size
: 1kb
User
:
王小二
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