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Table 3 Merging individual classifiers into the NB-MuSE classifier

From: Design of a multi-signature ensemble classifier predicting neuroblastoma patients' outcome

Classifier* External validation Paradigm° Function
  Accuracy (%)^   
Chen 85 BayesNet Learns Bayesian nets
Di Pietro 83 BayesNet Learns Bayesian nets
Fredlund 80 ClassificationViaRegression Class is binarized and one regression model is built for each class value
Asgharzadeh 83 ComplementNaiveBayes Builds a complement Näive Bayes classifier
Fransson 85 ComplementNaiveBayes Builds a complement Näive Bayes classifier
De Preter II 87 IBk k-nearest-neighbors classifier
Wei 83 IBk k-nearest-neighbors classifier
De Preter I 83 KStar Nearest neighbor with generalized distance function
Oberthuer 87 Logistic Builds linear logistic regression models
Hahn 82 MultiLayerPerceptron Backpropagation neural network
McArdle 80 MultiLayerPerceptron Backpropagation neural network
Oe 80 MultiLayerPerceptron Backpropagation neural network
Nevo II 87 NaiveBayes Standard probabilistic Näive Bayes classifier
Shimada 80 NBTree Builds a deciosion tree with Näive Bayes classifier at the leaves
Vermeulen 85 NBTree Builds a decision tree with Näive Bayes classifier at the leaves
Ohira 85 RandomForest Constructs random forest
Fischer 81 SimpleLogistic Builds linear logistic regression models with built-in attribute selection
Fardin 83 Voted Perceptron Voted perceptron algorihtm
Nevo I 80 Voted Perceptron Voted perceptron algorihtm
NB-MuSE 94 DecisonTable Builds a simple decision table majority classifier
  1. * Classifier associated to the signature described in the paper whose first name is listed.
  2. ^ External validation on the DS3 dataset.
  3. ° Paradigms that gave the top performance in external validation.