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Cette étude scientométrique se concentre sur le processus de structu- structu-ration des communautés envisagées pour mettre en lumière la

com-position largement hétérogène du domaine de l’apprentissage

artifi-ciel. Les techniques de modélisation et de visualisation utilisées

per-mettent de réaliser la cartographie de leurs citations. Dans un premier

temps, nous décrivons un résumé des techniques choisies pour

défi-nir les stratégies d’analyse et de cartographie adoptées (§3.2.2.1).

En-suite nous montrons comment, en analysant ce type de réseaux, nous

Corpus 1erAuteur Date Titre

Machine Learning

Pearson 1901 Principal Component Analysis

Mercer 1909 Functions of positive and negative type, and their connection with the theory of integral equations

Hotelling 1933 Analysis of a complex of statistical variables into principal components Fisher 1936 The use of multiple measurements in taxonomic problems

Friedman 1937 The use of ranks to avoid the assumption of normality implicit in the analysis of variance

Decision Tree

Fisher 1936 The use of multiple measurements in taxonomic problems

Friedman 1937 The use of ranks to avoid the assumption of normality implicit in the analysis of variance

Von Neumann 1944 The Theory of Games and Economic Behavior Wilcoxon 1945 Individual comparaisons by ranking methods Shanon 1948 A Mathematical Theory of Communication

Random Forest

Fisher 1936 The use of multiple measurements in taxonomic problems

Friedman 1937 The use of ranks to avoid the assumption of normality implicit in the analysis of variance

Jenny 1941 Factors of soil formation : a system of quantitative pedology Dice 1945 Measures of the amount of ecologic association between species Shanon 1948 A Mathematical Theory of Communication

Bayesian Net

Bayes 1763 An essay towards solving a problem in the doctrine of chances Wright 1921 Correlation and causation

Shanon 1948 A Mathematical Theory of Communication Kullback 1951 On information and sufficiency

Metropolis 1953 Equation of state calculations by fast computing machines

Naive Bayes

Bayes 1763 An essay towards solving a problem in the doctrine of chances Fisher 1936 The use of multiple measurements in taxonomic problems

Friedman 1937 The use of ranks to avoid the assumption of normality implicit in the analysis of variance

Shanon 1948 A Mathematical Theory of Communication Kullback 1951 On information and sufficiency

Neural Network

Pearson 1901 Principal Component Analysis

Hotelling 1933 Analysis of a complex of statistical variables into principal components Fisher 1936 The use of multiple measurements in taxonomic problems

McCulloch 1943 A logical calculus of the ideas immanent in nervous activity Levenberg 1944 A method for the solution of certain non–linear problems in least

squares

Genetic Algorithm

Darwin 1859 On the origin of the species by natural selection Pareto 1896 Cours d’économie politique

Fisher 1936 The use of multiple measurements in taxonomic problems Ziegler 1942 Optimum settings for automatic controllers

McCulloch 1943 A logical calculus of the ideas immanent in nervous activity

SVM

Pearson 1901 Principal Component Analysis

Mercer 1909 Functions of positive and negative type, and their connection with the theory of integral equations

Hotelling 1933 Analysis of a complex of statistical variables into principal components Wilcoxon 1945 Individual comparisons by ranking methods

Shanon 1948 TA Mathematical Theory of Communication Tableau8– Les 5 plus anciennes références parmi les1000plus citées par

Corpus 1erAuteur Date Titre

Machine Learning

Bache 2013 UCI machine learning repository

R Team 2013 R : A language and environment for statistical computing

Huang 2012 Extreme learning machine for regression and multiclass classification

Gaulton 2012 ChEMBL : a large-scale bioactivity database for drug discovery

Orru 2012 Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease

Decision Tree

Han 2012 Data mining : concepts and techniques

Witten 2011 Data mining : pratical machine learning tools and techniques

Archarya 2011 Automatic detection of epileptic EEG signals using higher order cumulant fea-tures

R Team 2013 R : A language and environment for statistical computing

Bache 2013 UCI machine learning repository

Random Forest

R Team 2013 R : A language and environment for statistical computing

Wouter 2013 Data mining in the Life Sciences with Random Forest : a walk in the park

Rodriguez-Galiano 2012 An assessment of the effectiveness of a random forest classifier for land-cover classification

Li 2912 Prediction of protein domain with mRMR feature selection and analysis

Criminisi 2012 Decision forests : A unified framework for classification, regression, density es-timation, manifold learning and semi-supervised learning

Bayesian Net

Dias 2013 Evidence synthesis for decision making

Khakzad 2013 Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

Pitchforth 2013 A proposed validation framework for expert elicited Bayesian Networks

Khakzad 2013 Risk-based design of process systems using discrete-time Bayesian networks

Nagarajan 2013 Bayesian networks in R

Naive Bayes

Bache 2013 UCI machine learning repository

Koutsoukas 2013 In silico target predictions : defining a benchmarking data set and comparison of performance of the multiclass naïve bayes and parzen-rosenblatt window

Zaidi 2013 Alleviating naive Bayes attribute independence assumption by attribute weigh-ting

Han 2012 Data mining : concepts and techniques

Jiang 2012 Improving Tree augmented Naive Bayes for class probability estimation

Neural Network

Nazari 2011 Modeling ductile to brittle transition temperature of functionally graded steels by artificial neural networks

Gharagheizi 2011 Determination of Parachor of Various Compounds Using an Artificial Neural Network

Witten 2011 Data Mining : Practical Machine Learning Tools and Techniques

Sezer 2011 Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility map-ping : Klang valley, Malaysia

Yilmaz 2010 Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey

Genetic Algorithm

Das 2011 Differential evolution : a survey of the state-of-the-art

Zhou 2011 Multiobjective evolutionary algorithms : A survey of the state-of-the-art

Derrac 2011 A practical tutorial on the use of nonparametric statistical tests as a methodolo-gyfor comparing evolutionary and swarm intelligence algorithms

Karaboga 2011 A novel clustering approach : Artificial Bee Colony (ABC) algorithm

Bhattacharya 2010 Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch

SVM

Chen 2013 iRSpot-PseDNC : identify recombination spots with pseudo dinucleotide com-position

Bache 2013 UCI machine learning repository

Xu 2013 Analysis of a complex of statistical variables into principal components

Huang 2012 iSNO-PseAAC : Predict Cysteine S-Nitrosylation Sites in Proteins by Incor-porating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition

Chou 2012 iLoc-Hum : using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites

Tableau9– Les5références les plus récentes parmi les1000plus citées par corpus.

parvenons à dégager les communautés thématiques sous-jacente propres