- SVM3 A support vector machine (SVM) is a concept in statistics and computer science for a set of related supervised learning methods that analyze data and recognize patterns
- Multi-regression 多元线性回归VBA实现 可以自动分析并生成最优回归方程 并计算中间量
- pthreads-emb-1.0.tar Ti DSP Bios平台下的pthread库
- Moments-simulation 基于矩量法仿真的笼形天线宽带化设计
- CN101344874A 一种以PC 232串口的DTR RTS DSR CTS 来实现I2C器件的读写操作
- WSLpurchaseMangementSystem 简单的java程序编写的登录界面
文件名称:8-PLDAPPPPPPP
介绍说明--下载内容来自于网络,使用问题请自行百度
Dimensionality reduction is one of the important preprocessing
steps to handle high-dimensional data. Linear discriminant
analysis (LDA) is a classical and popular approach for this purpose.
LDA finds an optimal linear transformation, which maximizes
the ratio of the variance in the between-class distance to
the variance in the within-class distance. On the other hand,
in order to overcome the limitation in LDA resulting the
assumption of equal covariance, several heteroscedastic extensions,
such as heteroscedastic discriminant analysis (HDA), have
been proposed.-Dimensionality reduction is one of the important preprocessing
steps to handle high-dimensional data. Linear discriminant
analysis (LDA) is a classical and popular approach for this purpose.
LDA finds an optimal linear transformation, which maximizes
the ratio of the variance in the between-class distance to
the variance in the within-class distance. On the other hand,
in order to overcome the limitation in LDA resulting the
assumption of equal covariance, several heteroscedastic extensions,
such as heteroscedastic discriminant analysis (HDA), have
been proposed.
steps to handle high-dimensional data. Linear discriminant
analysis (LDA) is a classical and popular approach for this purpose.
LDA finds an optimal linear transformation, which maximizes
the ratio of the variance in the between-class distance to
the variance in the within-class distance. On the other hand,
in order to overcome the limitation in LDA resulting the
assumption of equal covariance, several heteroscedastic extensions,
such as heteroscedastic discriminant analysis (HDA), have
been proposed.-Dimensionality reduction is one of the important preprocessing
steps to handle high-dimensional data. Linear discriminant
analysis (LDA) is a classical and popular approach for this purpose.
LDA finds an optimal linear transformation, which maximizes
the ratio of the variance in the between-class distance to
the variance in the within-class distance. On the other hand,
in order to overcome the limitation in LDA resulting the
assumption of equal covariance, several heteroscedastic extensions,
such as heteroscedastic discriminant analysis (HDA), have
been proposed.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
8-PLDA+++++++/address.docx
8-PLDA+++++++/no/20071004_Winston_PLDA.ppt
8-PLDA+++++++/no/plda-3.1-C++/5956491plda-3.1.tar.gz
8-PLDA+++++++/no/plda-3.1-C++/plda/accumulative_model.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/accumulative_model.h
8-PLDA+++++++/no/plda-3.1-C++/plda/cmd_flags.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/cmd_flags.h
8-PLDA+++++++/no/plda-3.1-C++/plda/common.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/common.h
8-PLDA+++++++/no/plda-3.1-C++/plda/COPYING
8-PLDA+++++++/no/plda-3.1-C++/plda/document.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/document.h
8-PLDA+++++++/no/plda-3.1-C++/plda/infer.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/INSTALL
8-PLDA+++++++/no/plda-3.1-C++/plda/lda.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/Makefile
8-PLDA+++++++/no/plda-3.1-C++/plda/model.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/model.h
8-PLDA+++++++/no/plda-3.1-C++/plda/mpi_lda.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/README
8-PLDA+++++++/no/plda-3.1-C++/plda/sampler.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/sampler.h
8-PLDA+++++++/no/plda-3.1-C++/plda/testdata/test_data.txt
8-PLDA+++++++/no/plda-3.1-C++/plda/view_model.py
8-PLDA+++++++/no/plda-3.1-C++/plda-3.1.tar.gz
8-PLDA+++++++/no/probabelistic-lda.pdf
8-PLDA+++++++/P-LDA/1-plda-transfer/plda-orginal.doc
8-PLDA+++++++/P-LDA/1-plda-transfer/plda-ostad.pdf
8-PLDA+++++++/P-LDA/1-plda-transfer/POWER LINEAR DISCRIMINANT ANALYSIS.docx
8-PLDA+++++++/P-LDA/1-plda-transfer/Xj.docx
8-PLDA+++++++/P-LDA/1-plda-transfer/آنالیز متمایز ساز خطی.docx
8-PLDA+++++++/P-LDA/70266646P-LDA.rar
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/cmc_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/cmc_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/diabetes_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/diabetes_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/glass_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/glass_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/ionosphere_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/ionosphere_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/Iris_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/Iris_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/tae_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/tae_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/vowel100_test.data
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/vowel100_trin.data
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/waveform_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/waveform_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/wine_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/wine_train.m
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowe1.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowel.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowel.scale.t
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel.docx
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100test.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_test.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_trin.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_trin.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/cmc.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/diabetes.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/diabetes_n.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/glass.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/ionosphere.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/Iris.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/tae.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/vowel100_test.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/vowel100_trin.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/waveform.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/wine.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/wine_n.data
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/vowel-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/vow
8-PLDA+++++++/no/20071004_Winston_PLDA.ppt
8-PLDA+++++++/no/plda-3.1-C++/5956491plda-3.1.tar.gz
8-PLDA+++++++/no/plda-3.1-C++/plda/accumulative_model.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/accumulative_model.h
8-PLDA+++++++/no/plda-3.1-C++/plda/cmd_flags.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/cmd_flags.h
8-PLDA+++++++/no/plda-3.1-C++/plda/common.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/common.h
8-PLDA+++++++/no/plda-3.1-C++/plda/COPYING
8-PLDA+++++++/no/plda-3.1-C++/plda/document.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/document.h
8-PLDA+++++++/no/plda-3.1-C++/plda/infer.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/INSTALL
8-PLDA+++++++/no/plda-3.1-C++/plda/lda.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/Makefile
8-PLDA+++++++/no/plda-3.1-C++/plda/model.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/model.h
8-PLDA+++++++/no/plda-3.1-C++/plda/mpi_lda.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/README
8-PLDA+++++++/no/plda-3.1-C++/plda/sampler.cc
8-PLDA+++++++/no/plda-3.1-C++/plda/sampler.h
8-PLDA+++++++/no/plda-3.1-C++/plda/testdata/test_data.txt
8-PLDA+++++++/no/plda-3.1-C++/plda/view_model.py
8-PLDA+++++++/no/plda-3.1-C++/plda-3.1.tar.gz
8-PLDA+++++++/no/probabelistic-lda.pdf
8-PLDA+++++++/P-LDA/1-plda-transfer/plda-orginal.doc
8-PLDA+++++++/P-LDA/1-plda-transfer/plda-ostad.pdf
8-PLDA+++++++/P-LDA/1-plda-transfer/POWER LINEAR DISCRIMINANT ANALYSIS.docx
8-PLDA+++++++/P-LDA/1-plda-transfer/Xj.docx
8-PLDA+++++++/P-LDA/1-plda-transfer/آنالیز متمایز ساز خطی.docx
8-PLDA+++++++/P-LDA/70266646P-LDA.rar
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/cmc_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/cmc_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/diabetes_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/diabetes_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/glass_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/glass_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/ionosphere_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/ionosphere_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/Iris_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/Iris_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/tae_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/tae_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/vowel100_test.data
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/vowel100_trin.data
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/waveform_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/waveform_train.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/wine_test.m
8-PLDA+++++++/P-LDA/P-LDA/60-40-dataset/wine_train.m
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowe1.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowel.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/orginal/vowel.scale.t
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel.docx
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100test.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_test.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_trin.arff
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/6-vowel_nor/vowel100_trin.libsvm
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/cmc.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/diabetes.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/diabetes_n.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/glass.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/ionosphere.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/Iris.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/tae.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/vowel100_test.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/vowel100_trin.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/waveform.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/wine.data
8-PLDA+++++++/P-LDA/P-LDA/create_dataset/wine_n.data
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/cmc-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/diabet-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/glass-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/iris-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/isonophere-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-test.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-train.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/tae-train.m
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/vowel-test.arff
8-PLDA+++++++/P-LDA/P-LDA/dataset_PLDA/vow
本网站为编程资源及源代码搜集、介绍的搜索网站,版权归原作者所有! 粤ICP备11031372号
1999-2046 搜珍网 All Rights Reserved.