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Library/ Machine Learning (Supervised + Unsupervised)/ Supervised Learning by Building/ S05 · Build: Distance, Probability & Margin Models

subtopic

Support Vector Machines (SVC | SVR)

10 min applied15 min research3 curated resources

Fit linear and RBF SVMs; tune C and gamma on a small grid; use probability calibration for SVC. Concepts: Maximum margin; support vectors; kernel trick; epsilon-insensitive regression Project A: RBF SVC with class_weight: competitive recall on 800 rows. Project B: SVR on a sample of 10k hours (full data is slow) — compare time and MAE vs boosting.

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Support Vector Machines (SVC | SVR) · 1x1labs.ai