B. Hanczar

发表

Ensemble methods for biclustering tasks

Blaise Hanczar, Mohamed Nadif, M. Nadif, 2012, Pattern Recognit..

Needle and surgical biopsy techniques differentially affect adipose tissue gene expression profiles.

K. Clément, Jean-Daniel Zucker, B. Hanczar, 2009, The American journal of clinical nutrition.

New Results - Applications to E-science

Blaise Hanczar, Balázs Kégl, Karima Rafes, 2014 .

Évolution de la stabilité de la sélection de variables en fonction de la taille d'échantillon et de la dimension

Jean-Daniel Zucker, B. Hanczar, David Dernoncourt, 2012 .

Assessment of deep learning and transfer learning for cancer prediction based on gene expression data

B. Hanczar, F. Zehraoui, Victoria Bourgeais, 2022, BMC Bioinformatics.

Microarray profiling of human white adipose tissue after exogenous leptin injection

K. Clément, W. Saris, B. Hanczar, 2006, European journal of clinical investigation.

GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression.

B. Hanczar, F. Zehraoui, Victoria Bourgeais, 2022, Bioinformatics.

Study of consensus functions in the context of ensemble methods for biclustering

M. Nadif, B. Hanczar, 2013 .

Controlling the Cost of Prediction in using a Cascade of Reject Classifiers for Personalized Medicine

Blaise Hanczar, Avner Bar-Hen, Avner Bar-Hen, 2016, BIOINFORMATICS.

Combination of One-Class Support Vector Machines for Classification with Reject Option

Blaise Hanczar, Michèle Sebag, M. Sebag, 2014, ECML/PKDD.

In vivo epinephrine-mediated regulation of gene expression in human skeletal muscle.

K. Clément, Jean-Daniel Zucker, G. Barsh, 2004, The Journal of clinical endocrinology and metabolism.

Interpretable and accurate prediction models for metagenomics data

Yann Chevaleyre, Blaise Hanczar, Jean-Daniel Zucker, 2018, bioRxiv.

Small-sample precision of ROC-related estimates

Blaise Hanczar, John N. Weinstein, Michael L. Bittner, 2010, Bioinform..

Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data

Blaise Hanczar, Farida Zehraoui, Victoria Bourgeais, 2021, BMC Bioinformatics.

Performance of Error Estimators for Classification

Blaise Hanczar, Edward R. Dougherty, Ulisses Braga-Neto, 2010 .

Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option

Blaise Hanczar, Jean-Daniel Zucker, Malik Sajjad Ahmed Nadeem, 2009, MLSB.

Performance visualization spaces for classification with rejection option

Blaise Hanczar, B. Hanczar, Blaise Hanczar, 2019, Pattern Recognit..

A3SOM, abstained explainable semi-supervised neural network based on self-organizing map

B. Hanczar, F. Tahi, F. Zehraoui, 2023, PloS one.

Precision-recall space to correct external indices for biclustering

Blaise Hanczar, Mohamed Nadif, M. Nadif, 2013, ICML.

A New Measure of Classifier Performance for Gene Expression Data

Blaise Hanczar, Avner Bar-Hen, Avner Bar-Hen, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Biological interpretation of deep neural network for phenotype prediction based on gene expression

Blaise Hanczar, Farida Zehraoui, Tina Issa, 2020, BMC Bioinformatics.

Classification with reject option in gene expression data

Blaise Hanczar, Edward R. Dougherty, E. Dougherty, 2008, Bioinform..

Analysis of feature selection stability on high dimension and small sample data

Blaise Hanczar, Jean-Daniel Zucker, David Dernoncourt, 2014, Comput. Stat. Data Anal..

On the Comparison of Classifiers for Microarray Data

Blaise Hanczar, Edward R. Dougherty, E. Dougherty, 2010 .

Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices

Blaise Hanczar, Mohamed Nadif, M. Nadif, 2018, ECML/PKDD.

Stability of Ensemble Feature Selection on High-Dimension and Low-Sample Size Data - Influence of the Aggregation Method

Blaise Hanczar, Jean-Daniel Zucker, David Dernoncourt, 2014, ICPRAM.

An Encoding Adversarial Network for Anomaly Detection

Blaise Hanczar, Jean-Christophe Janodet, Elies gherbi, 2019, ACML.

GAN-based data augmentation for transcriptomics: survey and comparative assessment

M. Sebag, B. Hanczar, Alice Lacan, 2023, Bioinform..

SurvCaus : Representation Balancing for Survival Causal Inference

B. Hanczar, A. Guilloux, Ayoub Abraich, 2022, ArXiv.

Phenotypes Prediction from Gene Expression Data with Deep Multilayer Perceptron and Unsupervised Pre-training

Blaise Hanczar, Farida Zehraoui, Mathieu Henriette, 2018 .

An approach to optimizing abstaining area for small sample data classification

Blaise Hanczar, Jean-Daniel Zucker, Jean-Daniel Zucker, 2018, Expert Syst. Appl..

The reliability of estimated confidence intervals for classification error rates when only a single sample is available

Blaise Hanczar, Edward R. Dougherty, E. Dougherty, 2013, Pattern Recognit..

Experimental analysis of feature selection stability for high-dimension and low-sample size gene expression classification task

Blaise Hanczar, Jean-Daniel Zucker, David Dernoncourt, 2012, 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE).

Decorrelation of the True and Estimated Classifier Errors in High-Dimensional Settings

Blaise Hanczar, Edward R. Dougherty, Jianping Hua, 2007, EURASIP J. Bioinform. Syst. Biol..