Add support for kernlab linear SVM models#252
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Adds tidypredict support for
kernlab::ksvm()models fit with the linear (vanilladot) kernel, includingsvm_linear()parsnip models using the"kernlab"engine, for regression and binary classification. With a linear kernel the decision function collapses to a weighted sum of the predictors, so both modes reuse the existing linear-model formula builder after undoing kernlab's internal scaling; binary classification folds kernlab's Platt-scaling probability into the glm logit path and predicts the second factor level to match the existing glm/LiblineaR convention.Non-linear kernels and multiclass classification are not supported, and classification requires a probability model (
prob.model = TRUE), since one-vs-one voting can't be expressed as a single linear formula. (#232)