搜索结果: 1-12 共查到“统计学其他学科 classification”相关记录12条 . 查询时间(0.046 秒)
Discriminative Sparse Coding on Multi-Manifold for Data Representation and Classification
Discriminative Sparse Coding Multi-Manifold for Data Representation Classification
2012/9/18
Sparse coding has been popularly used as an effective data represen-tation method in various applications, such as computer vision, medical imaging and bioinformatics, etc. However, the conventional s...
Joint-ViVo: Selecting and Weighting Visual Words Jointly for Bag-of-Features based Tissue Classification in Medical Images
Computer-Aided Diagnosis Tissue Classification Bag-of-Features Visual Vocabulary Visual Word Weighting
2012/9/18
Automatically classifying the tissues types of Region of Interest (ROI) in med-ical imaging has been an important application in Computer-Aided Diagno-sis (CAD), such as classification of breast paren...
Information-theoretic Dictionary Learning for Image Classification
Dictionary learning information theory mutual Dictionary learning information theory mutual
2012/9/18
We present a two-stage approach for learning dic-tionaries for object classification tasks based on the principle of information maximization. The proposed method seeks a dictionary that is compact, d...
Balancing Lifetime and Classification Accuracy of Wireless Sensor Networks
Balancing Lifetime Classification Accuracy Wireless Sensor Networks
2012/9/18
Wireless sensor networks are composed of dis-tributed sensors that can be used for signal detection or classification. The likelihood functions of the hypotheses are often not known in advance, and de...
Fast nonparametric classification based on data depth
Alpha-procedure zonoid depth DD-plot pattern recog-nition supervised learning, misclassification rate
2012/9/19
A new procedure, calledDDα-procedure, is developed to solve the problem of classifyingd-dimensional objects into q≥2 classes. The pro-cedure is completely nonparametric; it usesq-dimensional depth plo...
Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood
Gaussian process multiclass classification multinomial probit approximate inference expectation propagation
2012/9/19
We consider probabilistic multinomial probit classification using Gaussian process (GP) priors. The challenges with the multiclass GP classification are the integration over the non-Gaussian posterior...
Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches i...
Distribution fitting 12. Sampling distribution of compounds abundance from plant species measured by instrumentation. Application to plants metabolism classification
chemical compounds abundances lognormal distribution
2011/7/6
A series of ten plant species belonging to Magnoliopsida - Dicotyledons class were analyzed in terms of chemical compounds distribution of abundance, starting from the assumption that these distributi...
Learning Item-Attribute Relationship in Q-Matrix Based Diagnostic Classification Models
Cognitive assessment consistency DINA model DINO model
2011/7/5
Recent surge of interests in cognitive assessment has led to the developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which s...
Generalization error for multi-class margin classification
Convex and nonconvex losses import vector machines $psi$-learning sparse learning support vector machines
2009/9/16
In this article, we study rates of convergence of the generalization error of multi-class margin classifiers. In particular, we develop an upper bound theory quantifying the generalization error of va...
Classification with minimax fast rates for classes of Bayes rules with sparse representation
Classification Sparsity Decision dyadic trees Minimax rates Aggregation
2009/9/16
We consider the classification problem on the cube $[0,1]^d$ when the Bayes rule is known to belong to some new functions classes. These classes are made of prediction rules satisfying some conditions...
P-values for classification
nearest neighbors nonparametric optimality permutation test prediction region ROC curve typicality index validity
2009/9/16
Let $(X,Y)$ be a random variable consisting of an observed feature vector $X in XX$ and an unobserved class label $Y in {1,2,ldots,L}$ with unknown joint distribution. In addition, let $DD$ be a train...
