Semantic Scholar Open Access 2015 474 sitasi

Hyperparameter Search in Machine Learning

M. Claesen B. Moor

Abstrak

We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based on given data. Most common learning algorithms feature a set of hyperparameters that must be determined before training commences. The choice of hyperparameters can significantly affect the resulting model's performance, but determining good values can be complex; hence a disciplined, theoretically sound search strategy is essential.

Penulis (2)

M

M. Claesen

B

B. Moor

Format Sitasi

Claesen, M., Moor, B. (2015). Hyperparameter Search in Machine Learning. https://www.semanticscholar.org/paper/0173ca962e4ab3d084c89568345e06f67d3d7efc

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Informasi Jurnal
Tahun Terbit
2015
Bahasa
en
Total Sitasi
474×
Sumber Database
Semantic Scholar
Akses
Open Access ✓