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Clasificación de máquinas de vectores de apoyo

Máquinas de vectores de apoyo para clasificación binaria o multiclase

Para aumentar la precisión y las opciones de funciones de kernel en conjuntos de datos de dimensiones bajas y medianas, entrene un modelo SVM binario o un modelo multiclase de códigos de salida de corrección de errores (ECOC, por sus siglas en inglés) que contenga aprendices binarios de SVM mediante la appClassification Learner. Para mayor flexibilidad, utilice la interfaz de línea de comandos para entrenar un modelo SVM binario mediantefitcsvmo un modelo ECOC multiclase compuesto por aprendices binarios de SVM mediantefitcecoc.

Para reducir el tiempo de proceso en conjuntos de datos de altas dimensiones, entrene de forma eficiente un modelo de clasificación lineal binaria, por ejemplo, un modelo SVM lineal, mediantefitclinearo entrene un modelo ECOC multiclase compuesto por modelos SVM mediantefitcecoc.

Para las clasificaciones no lineales con big data, entrene un modelo de clasificación binaria de kernel gaussiano mediantefitckernel.

Apps

Classification Learner Train models to classify data using supervised machine learning

Bloques

ClassificationSVM Predict Classify observations using support vector machine (SVM) classifier for one-class and binary classification

Funciones

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fitcsvm Train support vector machine (SVM) classifier for one-class and binary classification
fitSVMPosterior Fit posterior probabilities
predict Classify observations using support vector machine (SVM) classifier
templateSVM Support vector machine template
fitclinear Fit binary linear classifier to high-dimensional data
predict Predict labels for linear classification models
templateLinear Linear classification learner template
fitckernel Fit binary Gaussian kernel classifier using random feature expansion
predict Predict labels for Gaussian kernel classification model
templateKernel Kernel model template
fitcecoc 适应多类支持向量机的模型金宝appor other classifiers
predict Classify observations using multiclass error-correcting output codes (ECOC) model
templateECOC Error-correcting output codes learner template

Clases

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ClassificationSVM Support vector machine (SVM) for one-class and binary classification
CompactClassificationSVM Compact support vector machine (SVM) for one-class and binary classification
ClassificationPartitionedModel Cross-validated classification model
ClassificationLinear Linear model for binary classification of high-dimensional data
ClassificationPartitionedLinear Cross-validated linear model for binary classification of high-dimensional data
ClassificationKernel Gaussian kernel classification model using random feature expansion
ClassificationPartitionedKernel Cross-validated, binary kernel classification model
ClassificationECOC Multiclass model for support vector machines (SVMs) and other classifiers
CompactClassificationECOC Compact multiclass model for support vector machines (SVMs) and other classifiers
ClassificationPartitionedECOC Cross-validated multiclass ECOC model for support vector machines (SVMs) and other classifiers
ClassificationPartitionedLinearECOC Cross-validated linear error-correcting output codes model for multiclass classification of high-dimensional data
ClassificationPartitionedKernelECOC Cross-validated kernel error-correcting output codes (ECOC) model for multiclass classification

Temas

Train Support Vector Machines Using Classification Learner App

Create and compare support vector machine (SVM) classifiers, and export trained models to make predictions for new data.

Support Vector Machines for Binary Classification

Perform binary classification via SVM using separating hyperplanes and kernel transformations.

Predict Class Labels Using ClassificationSVM Predict Block

This example shows how to use the ClassificationSVM Predict block for label prediction in Simulink®.