Training linear SVMs in linear time.

Thorsten Joachims
2006
2 references

Abstract

Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for high-dimensional sparse data commonly encountered in applications like text classification, word-sense disambiguation, and drug design. These applications involve a large number of examples n as well as a large number of features N, while each example has only s

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2 references

Code References

â–¶ scikit-learn/scikit-learn
2 files
â–¶ benchmarks/bench_covertype.py
1
# Create train-test split (as [Joachims, 2006])
â–¶ benchmarks/bench_mnist.py
1
# Create train-test split (as [Joachims, 2006])
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