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 |
|---|---|---|---|
| Â | Accuracy (%)^ | Â | Â |
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 |