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matlab例程 PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A componen
PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std ...
matlab例程 The BNL toolbox is a set of Matlab functions for defining and estimating the parameters of a Bayesi
The BNL toolbox is a set of Matlab functions for defining and estimating the
parameters of a Bayesian network for discrete variables in which the conditional
probability tables are specified by logistic regression models. Logistic regression can be
used to incorporate restrictions on the conditional ...
其他书籍 The book consists of three sections. The first, foundations, provides a tutorial overview of the pri
The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are construct ...
matlab例程 matlab中使用LM训练方法计算XOR
matlab中使用LM训练方法计算XOR，3-bit Parity，regression等问题的收敛速度，比较其收敛率。
论文 基于多尺度字典的图像超分辨率重建
Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introdu ...
源码 LibSVM
Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification.
书籍 interpretable-machine-learning
Machinelearninghasgreatpotentialforimprovingproducts,processesandresearch.Butcomputers
usually do not explain their predictions which is a barrier to the adoption of machine learning.
This book is about making machine learning models and their decisions interpretable.
After exploring the concepts of ...