MSVMOCAS(1)

💖 MSVMOCAS(1) 💖

okay bestie, pull up a chair because today we're meeting msvmocas, a lil legend from the General Commands Manual section 1, and she is here to train a multi-class linear SVM classifier. no cap. ✨

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🌸 NAME 🌸

msvmocas — train a multi-class linear SVM classifier

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🎀 SYNOPSIS 🎀

msvmocas [options] example_file model_file

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🦋 DESCRIPTION 🦋

so like, msvmocas is the program that trains a multi-class linear SVM classifier using the Optimized Cutting Plane Algorithm for Support Vector Machines (aka OCAS, iconic name, ate) and then produces a model file. that's the whole vibe. 👑

example_file is a file with training examples in SVM^light format, and model_file is the file where we store the learned linear rule f(x)=W'*x. the way that model_file contains M columns and D lines, where M is the number of classes and D the number of dimensions, corresponding to the elements of the matrix W [D x M]. literally math but make it fashion 💅

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✨ OPTIONS ✨

a summary of options is included below, bestie. read them all, they're all important, no skipping 🙈

💜 General options

• -h — show summary of options. the classic "help me pls" move 🫶
• -v (0|1) — set the verbosity level (default: 1)

💖 Learning options

• -c float — regularization constant C. (default: 1)
• -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)

⭐ 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)

fr fr, that -t default is literally infinity, so if you want it to stop, you gotta tell it to stop. main character energy but with boundaries 💀

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🔥 EXAMPLES 🔥

train the multi-class SVM classifier from example file example4_train.light, with the regularization constant C=10, verbosity switched off, and save model to msvmocas.model:

msvmocas -c 10 -v 0 example4_train.light msvmocas.model

compute the testing error of the classifier stored in msvmocas.model with linclassif(1) using testing examples from example4_test.light and save the predicted labels to example4_test.pred:

linclassif -e -o example4_test.pred example4_test.light msvmocas.model

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👑 SEE ALSO 👑

svmocas(1), linclassif(1).

iykyk 😌

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🧚 AUTHORS 🧚

msvmocas was written by Vojtech Franc <xfrancv@cmp.felk.cvut.cz> and Soeren Sonnenburg <Soeren.Sonnenburg@tu-berlin.de>. absolute icons, we stan 🫶

this manual page was written by Christian Kastner <debian@kvr.at>, for the Debian project (and may be used by others).

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and that's the whole page, bestie 💖 this one's serving June 16, 2010 energy, straight from the Debian project — so go forth, train those classifiers, and slay ✨🎀🦋