Five Interactive Apps for Machine Learning
No matter what type of problem you're trying to solve, MATLAB®is here to help. Discover apps to interactively model, fit, and label data for machine learning.
Classification Learner app
Train models to classify data
Perform supervised machine learning by supplying input data and known responses to the data. With this data, you can train a model that generates predictions for the response to new data and see the validated model results.
You can automatically train a selection of or all classifiers, compare validation results, and choose the best model that works for your classification problem.
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You can automatically train a selection of or all classifiers, compare validation results, and choose the best model that works for your classification problem.
Regression Learner app
Train multiple regression models
Use the Regression Learner app to interactively explore your data, select features, specify validation schemes, optimize hyperparameters, and assess model performance.
Train one or more regression models, compare validation results, and choose the best model that works for your regression problem.
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Train one or more regression models, compare validation results, and choose the best model that works for your regression problem.
曲线Fitting app
Fit curves and surfaces to data
Use linear or nonlinear regression, interpolation, smoothing, and custom equations to fit curves and compare multiple fits.
See confidence intervals and residuals, remove outliers, and assess fits with validation data.
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See confidence intervals and residuals, remove outliers, and assess fits with validation data.
Image Labeler app
Label ground truth data in images
Use built-in detection and tracking algorithms to label your ground truth data, or create custom automation algorithms.
Evaluate the performance of your label automation algorithms with a visual summary and export the labeled ground truth for use in system verification, object detection, or a semantic segmentation network.
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Evaluate the performance of your label automation algorithms with a visual summary and export the labeled ground truth for use in system verification, object detection, or a semantic segmentation network.
Signal Labeler app
Label signal attributes, regions, and points of interest
Interactively label signals for analysis or for use in machine learning applications.
Use logical or categorical labels for signal attributes, automatically label signal peaks and add, edit, delete, or display labels or subsets of signal labels.
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Use logical or categorical labels for signal attributes, automatically label signal peaks and add, edit, delete, or display labels or subsets of signal labels.
