NTNU

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I am a research fellow at NTNU (Norway) with broad interests in data mining and machine learning using probabilistic graphical models. Lately, my research has focused on scalable machine learning methods for solving real use cases in the financial (BCC group) and automotive industry (Daimler group). I am coauthor of more than 50 scientist papers in different journal and international conferences covering applied areas such as bioinformatics, information retrieval, crime prediction and sales forces allocation. I have been speaker in dozens of international conferences related to machine learning research over the last fifteen years. Recently, our team has been invited to present the AMIDST...

imprecise probabilities imprecise dirichlet model bayesian networks classification interactive learning supervised classification uncertainty measures decision trees classification trees credal sets ensemble decision trees information retrieval credal decision trees classification noise information based uncertainty measures uncertainty measures read more: http://www.world imprecise classification nonparametric predictive inference model bayesian metrics bayesian dirichlet metrics selective gaussian naïve bayes diffuse-large b-cell lymphoma noisy observations gene expression microarray eqtl hapmap snp variable selection decision tree semi-naive bayes uncertainty entropy learning bayesian random forests ensemble methods diffuse large-b-cell lymphoma features selection selective naive bayes query independent features relevancy prediction relevance prediction highly agreed documents

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Evaluating query-independent object features for relevancy prediction

il y a 8 ans • 213 Vues

Selective Gaussian Naïve Bayes Model for Diffuse Large-B-Cell Lymphoma Classification: Some Improvements in Preprocessing and Variable Elimination

il y a 8 ans • 318 Vues

NTNU

Présentations

Evaluating query-independent object features for relevancy prediction

Selective Gaussian Naïve Bayes Model for Diffuse Large-B-Cell Lymphoma Classification: Some Improvements in Preprocessing and Variable Elimination

An Experimental Study about Simple Decision Trees for Bagging Ensemble on Datasets with Classification Noise

A Bayesian Random Split to Build Ensembles of Classification Trees

Interactive Learning of Bayesian Networks

Combining Decision Trees Based on Imprecise Probabilities and Uncertainty Measures

A Semi-naive Bayes Classifier with Grouping of Cases

Split Criterions for Variable Selection Using Decision Trees

Learning classifiers from discretized expression quantitative trait loci

An interactive approach for cleaning noisy observations in Bayesian networks with the help of an expert

Application of a Selective Gaussian Naïve Bayes Model for Diffuse-Large B-Cell Lymphoma Classification

Locally Averaged Bayesian Dirichlet Metrics

lassification with decision trees from a nonparametric predictive inference perspective

Bagging Decision Trees on Data Sets with Classification Noise

An Importance Sampling Approach to Integrate Expert Knowledge When Learning Bayesian Networks From Data

Varying parameter in classification based on imprecise probabilities

Documents

Conference poster 6

Effects of Highly Agreed Documents in Relevancy Prediction

A Bayesian approach to estimate probabilities in classification trees

J’aime

Google TensorFlow Tutorial

Building Custom Machine Learning Algorithms With Apache SystemML

Flink Streaming

FOWD November 2007

Web 2.0

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