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Visualization and Interpretability

Plot training progress, assess accuracy, explain predictions, and visualize features learned by a network

Monitor training progress using built-in plots of network accuracy and loss. Investigate trained networks using visualization techniques such as Grad-CAM, occlusion sensitivity, LIME, and deep dream.

Deep Learning Visualization Methods


Deep Network DesignerDesign and visualize deep learning networks


trainingProgressMonitorMonitor and plot training progress for deep learning custom training loops (Since R2022b)


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analyzeNetworkAnalyze deep learning network architecture
plotPlot neural network architecture
updateInfoUpdate information values for custom training loops (Since R2022b)
recordMetricsRecord metric values for custom training loops (Since R2022b)
groupSubPlotGroup metrics in training plot (Since R2022b)
yscaleSet training plot y-axis scale (linear or logarithmic) (Since R2024a)
accuracyMetricDeep learning accuracy metric (Since R2023b)
aucMetricDeep learning area under ROC curve (AUC) metric (Since R2023b)
fScoreMetricDeep learning F-score metric (Since R2023b)
precisionMetricDeep learning precision metric (Since R2023b)
recallMetricDeep learning recall metric (Since R2023b)
rmseMetricDeep learning root mean squared error metric (Since R2023b)
predictCompute deep learning network output for inference (Since R2019b)
minibatchpredictMini-batched neural network prediction (Since R2024a)
scores2labelConvert prediction scores to labels (Since R2024a)
confusionchartCreate confusion matrix chart for classification problem
sortClassesSort classes of confusion matrix chart
rocmetricsReceiver operating characteristic (ROC) curve and performance metrics for binary and multiclass classifiers (Since R2022b)
addMetricsCompute additional classification performance metrics (Since R2022b)
averageCompute performance metrics for average receiver operating characteristic (ROC) curve in multiclass problem (Since R2022b)
plotPlot receiver operating characteristic (ROC) curves and other performance curves (Since R2022b)
imageLIMEExplain network predictions using LIME (Since R2020b)
occlusionSensitivityExplain network predictions by occluding the inputs (Since R2019b)
deepDreamImageVisualize network features using deep dream
gradCAMExplain network predictions using Grad-CAM (Since R2021a)
driseExplain object detection network predictions using D-RISE (Since R2024a)


ConfusionMatrixChart PropertiesConfusion matrix chart appearance and behavior
ROCCurve PropertiesReceiver operating characteristic (ROC) curve appearance and behavior (Since R2022b)


Training Progress and Performance