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In machine learning, hyperparameter optimization [1] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts.
PDFedit is a free PDF editor for Unix-like operating systems (including Cygwin on top of Windows). It does not support editing protected or encrypted PDF files or word processor-style text manipulation, however. [1] PDFedit GUI is based on the Qt 3 toolkit and scripting engine , so every operation is scriptable.
Model selection - choosing which machine learning algorithm to use, often including multiple competing software implementations; Ensembling - a form of consensus where using multiple models often gives better results than any single model [6] Hyperparameter optimization of the learning algorithm and featurization Neural architecture search
In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).
Vowpal Wabbit (VW) is an open-source fast online interactive machine learning system library and program developed originally at Yahoo! Research, and currently at Microsoft Research.
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