Struct linfa_svm::hyperparams::SvmValidParams [−][src]
pub struct SvmValidParams<F: Float, T> { /* fields omitted */ }Expand description
SVM Hyperparameters
The SVM fitting process can be controlled in different ways. For classification the C and Nu
parameters control the ratio of support vectors and accuracy, eps controls the required
precision. After setting the desired parameters a model can be fitted by calling fit.
You can specify the expected return type with the turbofish syntax. If you want to enable Platt-Scaling for proper probability values, then use:
use linfa_svm::Svm;
use linfa::dataset::Pr;
let model = Svm::<f64, Pr>::params();or bool if you only wants to know the binary decision:
use linfa_svm::Svm;
let model = Svm::<f64, bool>::params();Example
ⓘ
use linfa_svm::Svm;
let model = Svm::<_, bool>::params()
.eps(0.1f64)
.shrinking(true)
.nu_weight(0.1)
.fit(&dataset);