[source] # SVC The multiclass Support Vector Machine (SVM) Classifier is a maximum margin classifier that can efficiently perform non-linear classification by implicitly mapping feature vectors into high-dimensional feature space using the *kernel trick*. !!! note This learner requires the [SVM extension](https://php.net/manual/en/book.svm.php) which uses the libsvm engine under the hood. **Interfaces:** [Estimator](../estimator.md), [Learner](../learner.md) **Data Type Compatibility:** Continuous ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | c | 1.0 | float | The parameter that defines the width of the margin used to separate the classes. | | 2 | kernel | RBF | Kernel | The kernel function used to operate in higher dimensions. | | 3 | shrinking | true | bool | Should we use the shrinking heuristic? | | 4 | tolerance | 1e-3 | float | The minimum change in the cost function necessary to continue training. | | 5 | cache size | 100.0 | float | The size of the kernel cache in MB. | ## Example ```php use Rubix\ML\Classifiers\SVC; use Rubix\ML\Kernels\SVM\Linear; $estimator = new SVC(1.0, new Linear(), true, 1e-3, 100.0); ``` ## Additional Methods Save the model data to the filesystem: ```php public save(string $path) : void ``` Load the model data from the filesystem: ```php public load(string $path) : void ``` ## References [^1]: C. Chang et al. (2011). LIBSVM: A library for support vector machines.