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Classification of Gene Microarrays by P enalized Logisti Regression
cancer diagnosis feature selection logistic regression microarray support vector machines
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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
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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...
Mean field variational Bayesian inference for support vector machine classification
Approximate Bayesian inference variable selection missing data mixed model Markov chain Monte Carlo
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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
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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...
Ensembling Classification Models Based on Phalanxes of Variables with Applications in Drug Discovery
classification ranking ensemble random forest cluster pha-lanx
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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...
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
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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...