SVMOCAS(1)

✨ SVMOCAS(1) — like, the manual page bestie ✨

okay so welcome to the General Commands Manual entry for svmocas(1), and honestly? she's iconic. let's get into it 💅

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🌸 NAME 🌸

svmocas — train a binary linear SVM classifier

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🦋 SYNOPSIS 🦋

svmocas [options] example_file model_file

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💖 DESCRIPTION 💖

svmocas is that girl. she trains a binary linear SVM classifier using the Optimized Cutting Plane Algorithm for Support Vector Machines (OCAS) and then produces a model file. no cap.

example_file is a file with training examples in SVM^light format. and model_file is the file where the learned linear rule f(x)=w'*x+w0 gets stored. so model_file contains d lines, where d is the number of data dimensions. the first n lines are coordinates of w and the last line is w0. periodt. 💫

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✨ OPTIONS ✨

a summary of options is included below. she has range, bestie.

🎀 General options

• -h — show summary of options. the "help me bestie" button fr.
• -v (0|1) — set the verbosity level (default: 1). how chatty she is.

💜 Learning options

• -c float — Regularization constant C. (default: 1)
• -C constants_file — if specified, each example has a different regularization constant, taken from the text file constants_file. Each line of the text file must contain a single constant (positive double) for the corresponding example. If -C is used, then the -c option is ignored. 💀
• -b (0|1) — Value of the L2-bias feature. A value of 0 implies not having bias. (default: 0)
• -n integer — Use only the first integer examples for training. By default, integer equals the number of examples in example_file.

🔥 Optimization options

• -m (0|1) — Solver to be used:
  • 0 ... standard cutting plane (equivalent to BMRM, SVM^perf)
  • 1 ... OCAS (default)
• -s integer — Cache size for cutting planes. (default: 2000)
• -p integer — Number of threads. (default: 1)

⭐ Stopping conditions

• -a float — Absolute tolerance TolAbs: halt if QP-QD <= TolAbs. (default: 0)
• -r float — Relative tolerance TolAbs: halt if QP-QD <= abs(QP)*TolRel. (default: 0.01)
• -q float — Desired objective value QPValue: halt is QP <= QPValue. (default: 0)
• -t float — Halts if the solver time (loading time is not counted) exceeds the time given in seconds. (default: infinity)

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🌈 EXAMPLES 🌈

Train the binary SVM classifier from riply_trn.light, with the regularization constant C=10, bias switched on, verbosity switched off, and save model to svmocas.model:

svmocas -c 10 -b 1 -v 0 riply_trn.light svmocas.model

Compute the testing error of the classifier stored in svmocas.model with linclassif(1) using testing examples from riply_tst.light and save the predicted labels to riply_tst.pred:

linclassif -e -o riply_tst.pred riply_tst.light svmocas.model

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👑 SEE ALSO 👑

msvmocas(1), linclassif(1). go read those next, iykyk 🫶

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🫶 AUTHORS 🫶

svmocas was written by Vojtech Franc <xfrancv@cmp.felk.cvut.cz> and Soeren Sonnenburg <Soeren.Sonnenburg@tu-berlin.de>.

This manual page was written by Christian Kastner <ckk@debian.org> for the Debian project (and may be used by others).

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okay that's the whole page bestie, go train something cute 🎀

and for the sign-off: this little beauty is dated June 16, 2010, and yeah, it's still SVMOCAS(1) in the General Commands Manual. iconic behavior, no notes. 💖 ✨ 🦋