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Vanilla Lasso for sparse classification under single index models
Vanilla Lasso sparse classification single index models
2016/1/20
This paper study sparse classification problems. We show that under single-index models, vanilla Lasso could give good estimate of unknown parameters. With this result, we see that even if the model i...
Classification of Gene Microarrays by P enalized Logisti Regression
cancer diagnosis feature selection logistic regression microarray support vector machines
2015/8/21
Classification of Gene Microarrays by P enalized Logisti Regression.
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
ASupervised Neural Autoregressive Topic Model Simultaneous Image Classification Annotation
2013/6/17
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural Aut...
Meta Path-Based Collective Classification in Heterogeneous Information Networks
Heterogeneous information networks Meta path Collective classi
2013/6/17
Collective classification has been intensively studied due to its impact in many important applications, such as web mining, bioinformatics and citation analysis. Collective classification approaches ...
Spatial Depth-Based Classification for Functional Data
Functional depths Functional outliers Spatial functional depth Supervised func-tional classification
2013/6/14
We enlarge the available number of functional depths by defining two new depth measures for curves. Both depths are based on a spatial approach: the functional spatial depth (FSD), that shows an inter...
Mean field variational Bayesian inference for support vector machine classification
Approximate Bayesian inference variable selection missing data mixed model Markov chain Monte Carlo
2013/6/14
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows circumvention of ma...
Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification
Bayesian Inference Model Averaging K-free model order estimation
2013/6/14
Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncertaint...
Heart Disease Prediction System using Associative Classification and Genetic Algorithm
Andhra Pradesh Associative classification Genetic algorithm Gini Index Z-Statistics
2013/5/2
Associative classification is a recent and rewarding technique which integrates association rule mining and classification to a model for prediction and achieves maximum accuracy. Associative classifi...
Variable Selection for Clustering and Classification
Classication Cluster analysis High-dimensional data Mixture models Model-based clus-tering Variable selection
2013/4/28
As data sets continue to grow in size and complexity, effective and efficient techniques are needed to target important features in the variable space. Many of the variable selection techniques that a...
Ensembling Classification Models Based on Phalanxes of Variables with Applications in Drug Discovery
classification ranking ensemble random forest cluster pha-lanx
2013/4/28
We have proposed an ensemble method which aggregates over clusters of predictor variables. We form the clusters (we call phalanxes) by joining variables together. The variables in a phalanx are good t...
Classification of Segments in PolSAR Imagery by Minimum Stochastic Distances Between Wishart Distributions
Region-Based Classification Stochastic Distances Hypothesis Tests Polarimetry Wishart distribution
2013/4/28
A new classifier for Polarimetric SAR (PolSAR) images is proposed and assessed in this paper. Its input consists of segments, and each one is assigned the class which minimizes a stochastic distance. ...
Complex Support Vector Machines for Regression and Quaternary Classification
Support Vector Machines Kernel methods Widely linear estimation com-plex data
2013/4/28
We present a support vector machines (SVM) rationale suitable for regression and quaternary classification problems that use complex data, exploiting the notions of widely linear estimation and pure c...
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Classification Asymmetric Label Noise Consistency Maximal Denoising
2013/4/27
In many real-world classification problems, the labels of training examples are randomly corrupted. Previous theoretical work on classification with label noise assumes that the two classes are separa...
Hybrid Maximum Likelihood Modulation Classification Using Multiple Radios
Modulation classification data fusion ML esti-mation EM algorithm
2013/4/28
The performance of a modulation classifier is highly sensitive to channel signal-to-noise ratio (SNR). In this paper, we focus on amplitude-phase modulations and propose a modulation classification fr...
Non-identifiability, equivalence classes, and attribute-specific classification in Q-matrix based Cognitive Diagnosis Models
CDM diagnostic classification DINA DINO NIAD-DINA Q-matrix consistency identifiability
2013/4/27
There has been growing interest in recent years in Q-matrix based cognitive diagnosis models. Parameter estimation and respondent classification under these models may suffer due to identifiability is...