High dimensional feature selection under interactive models

High dimensional feature selection under interactive models

Ph.D

Saved in:

Bibliographic Details
Main Author:	HE YAWEI
Other Authors:	STATISTICS & APPLIED PROBABILITY
Format:	Theses and Dissertations
Language:	English
Published:	2013
Subjects:	feature selection, EBIC, penalized methods
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/43584
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore
Language:	English

Similar Items

CORRELATION SCREENING AND FEATURE SELECTION FOR ULTRA-HIGH-DIMENSIONAL MODELS WITH COMPLEX STRUCTURES
by: GONG YUAN
Published: (2019)

Tournament screening cum EBIC for feature selection with high-dimensional feature spaces
by: Chen, Z., et al.
Published: (2014)

Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
by: Luo, S., et al.
Published: (2014)

Feature Selection in High-Dimensional Studies
by: LUO SHAN
Published: (2012)

STEM electron beam-induced current measurements of organic-inorganic perovskite solar cells
by: Duchamp, Martial, et al.
Published: (2021)

MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA
by: FANG YUHANG
Published: (2019)

FEATURE SELECTION IN HIGH-DIMENSIONAL MODELS AND INTERPRETING DEEP NEURAL NETWORKS
by: ZHANG AN
Published: (2021)

Minimax concave bridge penalty function for variable selection
by: CHUA LAI CHOON
Published: (2012)

Feature selection for classification
by: Dash, M., et al.
Published: (2014)

Feature Selection and Model Selection for Supervised Learning Algorithms
by: YANG JIANBO
Published: (2011)

Model selection in nonparametric hazard regression
by: Leng, C., et al.
Published: (2014)

Feature selection via discretization
by: Liu, H., et al.
Published: (2014)

Electron-acoustic and surface electron beam induced voltage signal formation in scanning electron microscopy analysis of semiconducting samples
by: Wong, W.K., et al.
Published: (2014)

Feature selection via sensitivity analysis of SVM probabilistic outputs
by: Shen, K.-Q., et al.
Published: (2011)

A penalized likelihood approach in covariance graphical model selection
by: LIN NAN
Published: (2011)

An effective feature selection method via mutual information estimation
by: Yang, J.-B., et al.
Published: (2014)

Incremental Feature Selection
by: Liu, H., et al.
Published: (2014)

Feature selection for the prediction of translation initiation sites
by: Li, G.-L., et al.
Published: (2013)

Feature selection for modular GA-based classification
by: Zhu, F., et al.
Published: (2014)

Variable Selection in Nonparametric and Semiparametric Regression Models
by: SU, Liangjun, et al.
Published: (2013)

Penalized high-dimensional empirical likelihood
by: Tang, C.Y., et al.
Published: (2014)

Feature selection for support vector regression using probabilistic prediction
by: Yang, J.-B., et al.
Published: (2014)

Feature selection via sensitivity analysis of MLP probabilistic outputs
by: Yang, J.-B., et al.
Published: (2014)

Feature selection using probabilistic prediction of support vector regression
by: Yang, J.-B., et al.
Published: (2014)

Some issues on scalable feature selection
by: Liu, H., et al.
Published: (2014)

Improving backpropagation learning with feature selection
by: Setiono, R., et al.
Published: (2014)

New feature selection method for multi-channel EEG epileptic spike detection system
by: Nguyen, Thi Anh Dao, et al.
Published: (2020)

Novel multi-class feature selection methods using sensitivity analysis of posterior probabilities
by: Shen, K.-Q., et al.
Published: (2011)

A comparative study of feature selection for hidden Markov model-based micro-milling tool wear monitoring
by: Zhu, K.P., et al.
Published: (2014)

Feature selection and classification via a GA-SVM hybrid
by: Teoh, E.-J., et al.
Published: (2014)

An incremental approach to contribution-based feature selection
by: Guan, S.-U., et al.
Published: (2014)

Feature selection for MLP neural network: The use of random permutation of probabilistic outputs
by: Yang, J.-B., et al.
Published: (2014)

The impact of automated feature selection techniques on the interpretation of defect models
by: JIARPAKDEE, Jirayus, et al.
Published: (2020)

Cost-sensitive feature selection by optimizing F-measures
by: Liu, Meng, et al.
Published: (2020)

FEATURE SELECTION : A PREPROCESSING STEP IN DATA MINING
by: MANORANJAN DASH
Published: (2020)

Correntropy based feature selection using binary projection
by: Yan, H., et al.
Published: (2014)

Large-scale online feature selection for ultra-high dimensional sparse data
by: WU, Yue, et al.
Published: (2017)

Penalized empirical likelihood and growing dimensional general estimating equations
by: Leng, C., et al.
Published: (2014)

Feature selection for modular neural network classifiers
by: Guan, S.-U., et al.
Published: (2014)

LESS IS MORE: IMPROVING THE PERFORMANCE OF LEARNING MODELS WITH FEWER FEATURES OR FEWER PARAMETERS
by: LIU SHIYU
Published: (2023)