文件名称:LDA
- 所属分类:
- 图形图像处理(光照,映射..)
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2012-11-26
- 文件大小:
- 55kb
- 下载次数:
- 0次
- 提 供 者:
- 苗*
- 相关连接:
- 无
- 下载说明:
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线性判别分析(LDA)用于特征选择,可以对数据集或者图像提取有用特征,用于分类或者聚类等机器学习应用中-Linear Discriminant Analysis (LDA) for feature selection, application in dataset or image feature extraction, for classification or clustering applications in machine learning
相关搜索: LDA
特征选择
lda
matlab
机器学习
lda
classification
matlab
dataset
判别分析
线性判别分析
feature
clustering
matlab
线性
特征
提取
特征选择
lda
matlab
机器学习
lda
classification
matlab
dataset
判别分析
线性判别分析
feature
clustering
matlab
线性
特征
提取
(系统自动生成,下载前可以参看下载内容)
下载文件列表
线性判别分析LDA
...............\abut
...............\all-correlate
...............\auc.m
...............\backward.m
...............\bernoulli.m
...............\binvar.m
...............\boxplot.m
...............\cauchy.m
...............\cdf_norm.m
...............\check_result
...............\chisq.m
...............\classify.m
...............\classify_new.m
...............\classify_rate.m
...............\clindisc.m
...............\concordance.m
...............\Contents.m
...............\Contents.m~
...............\corr.ptr
...............\corr.pts
...............\cpruned_lindisc.m
...............\culindisc.m
...............\data
...............\deuclid.m
...............\dmeuclid.m
...............\ex_duda.m
...............\format_result
...............\forward
...............\forward.m
...............\forwards.m
...............\forward_class.m
...............\forward_class_patt.m
...............\fwd-linear
...............\gauss.m
...............\gaussian2D.m
...............\getthresh.m
...............\kappa.m
...............\knn.m
...............\ks.m
...............\ksone.m
...............\l1out.m
...............\lclassify.m
...............\lindisc.m
...............\linfwd.m
...............\linnode.m
...............\linreg.m
...............\linsep.m
...............\mad.m
...............\make-col-ones
...............\mlindisc.m
...............\mquaddisc.m
...............\nn.m
...............\nn_class.m
...............\normal.m
...............\normalis.m
...............\nrows
...............\opcurve.m
...............\pauc.m
...............\pchisq.m
...............\pdiff.m
...............\pdiffbin.m
...............\plindisc.m
...............\plot_cauchy_gauss.m
...............\plot_lin_map.m
...............\pnorm.m
...............\probks.m
...............\pruned_lda.m
...............\pruned_lindisc.m
...............\quaddisc.m
...............\quadsep.m
...............\rclassify.m
...............\README
...............\regress.m
...............\skew.m
...............\svd_pinv.m
...............\tab-to-space
...............\test_class.m
...............\tmp-out
...............\tmp2
...............\ttest.m
...............\ttest1.m
...............\ttest_stat.m
...............\ugauss.m
...............\ugaussmix.m
...............\ulin_l1out.m
...............\vars_tmp
...............\xblob.m
...............\xforward.m
...............\xksone.m
...............\xlindisc1.m
...............\xlinsep1.m
...............\xorsep.m
...............\xquadsep1.m
...............\新建 文本文档.txt
...............\abut
...............\all-correlate
...............\auc.m
...............\backward.m
...............\bernoulli.m
...............\binvar.m
...............\boxplot.m
...............\cauchy.m
...............\cdf_norm.m
...............\check_result
...............\chisq.m
...............\classify.m
...............\classify_new.m
...............\classify_rate.m
...............\clindisc.m
...............\concordance.m
...............\Contents.m
...............\Contents.m~
...............\corr.ptr
...............\corr.pts
...............\cpruned_lindisc.m
...............\culindisc.m
...............\data
...............\deuclid.m
...............\dmeuclid.m
...............\ex_duda.m
...............\format_result
...............\forward
...............\forward.m
...............\forwards.m
...............\forward_class.m
...............\forward_class_patt.m
...............\fwd-linear
...............\gauss.m
...............\gaussian2D.m
...............\getthresh.m
...............\kappa.m
...............\knn.m
...............\ks.m
...............\ksone.m
...............\l1out.m
...............\lclassify.m
...............\lindisc.m
...............\linfwd.m
...............\linnode.m
...............\linreg.m
...............\linsep.m
...............\mad.m
...............\make-col-ones
...............\mlindisc.m
...............\mquaddisc.m
...............\nn.m
...............\nn_class.m
...............\normal.m
...............\normalis.m
...............\nrows
...............\opcurve.m
...............\pauc.m
...............\pchisq.m
...............\pdiff.m
...............\pdiffbin.m
...............\plindisc.m
...............\plot_cauchy_gauss.m
...............\plot_lin_map.m
...............\pnorm.m
...............\probks.m
...............\pruned_lda.m
...............\pruned_lindisc.m
...............\quaddisc.m
...............\quadsep.m
...............\rclassify.m
...............\README
...............\regress.m
...............\skew.m
...............\svd_pinv.m
...............\tab-to-space
...............\test_class.m
...............\tmp-out
...............\tmp2
...............\ttest.m
...............\ttest1.m
...............\ttest_stat.m
...............\ugauss.m
...............\ugaussmix.m
...............\ulin_l1out.m
...............\vars_tmp
...............\xblob.m
...............\xforward.m
...............\xksone.m
...............\xlindisc1.m
...............\xlinsep1.m
...............\xorsep.m
...............\xquadsep1.m
...............\新建 文本文档.txt