Neural Networks

Neural networks for binary and multiclass classification

Neural network models are structured as a series of layers that reflect the way the brain processes information. The neural network classifiers available in Statistics and Machine Learning Toolbox™ are fully connected, feedforward neural networks for which you can adjust the size of the fully connected layers and change the activation functions of the layers.

To train a neural network classification model, use the Classification Learner app. For greater flexibility, train a neural network classifier using fitcnet in the command-line interface. After training, you can classify new data by passing the model and the new predictor data to predict.

If you want to create more complex deep learning networks and have Deep Learning Toolbox™, you can try the Deep Network Designer (Deep Learning Toolbox) app.

Apps

Classification LearnerTrain models to classify data using supervised machine learning

Blocks

ClassificationNeuralNetwork PredictClassify observations using neural network classification model (Since R2021b)

Functions

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fitcnetTrain neural network classification model (Since R2021a)
compactReduce size of machine learning model
limeLocal interpretable model-agnostic explanations (LIME)
partialDependenceCompute partial dependence
permutationImportancePredictor importance by permutation (Since R2024a)
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
shapleyShapley values (Since R2021a)
crossvalCross-validate machine learning model
kfoldLossClassification loss for cross-validated classification model
kfoldPredictClassify observations in cross-validated classification model
kfoldEdgeClassification edge for cross-validated classification model
kfoldMarginClassification margins for cross-validated classification model
kfoldfunCross-validate function for classification
lossClassification loss for neural network classifier (Since R2021a)
resubLossResubstitution classification loss
edgeClassification edge for neural network classifier (Since R2021a)
marginClassification margins for neural network classifier (Since R2021a)
resubEdgeResubstitution classification edge
resubMarginResubstitution classification margin
predictClassify observations using neural network classifier (Since R2021a)
resubPredictClassify training data using trained classifier

Objects

ClassificationNeuralNetworkNeural network model for classification (Since R2021a)
CompactClassificationNeuralNetworkCompact neural network model for classification (Since R2021a)
ClassificationPartitionedModelCross-validated classification model

Topics