How to Calibrate your Neural Network Classifier: Getting True Probabilities from a Classification Model.
Natalia CulakovaDan MurphyJoao GanteCarlos LedezmaVahan HovhannisyanAlan MoscaPublished in: KDD (2020)
Keyphrases
- neural network
- fuzzy artmap
- learning vector quantization
- backpropagation neural network
- artificial neural networks
- training process
- class probabilities
- multi layer perceptron
- probability estimates
- probabilistic neural network
- bayes theorem
- probability distribution
- training data
- class conditional
- back propagation
- class labels
- decision trees
- mlp neural networks
- binary decision tree
- class membership
- feature maps
- nearest neighbour
- prediction model
- neural network model
- learning algorithm
- classification algorithm
- feature selection
- knn
- multi class
- fuzzy logic
- feature space
- support vector
- feature values
- classification method
- neural network is trained
- machine learning
- neural nets
- belief networks
- incremental learning
- multilayer perceptron
- data sets
- fuzzy classifier
- svm classifier
- fault diagnosis
- camera calibration
- classification rate
- classification scheme
- fuzzy rules
- cost sensitive