December 2018
Intermediate to advanced
318 pages
8h 28m
English
Content preview from Hands-On Machine Learning for Cybersecurity
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Difference between test and validation datasets
The validation dataset is a part of the data that is kept aside and not used to train the model. This data is later used to tune hyperparameters and estimate model efficiency.
The validation dataset is not the same as the test dataset (other data that is also kept aside during the training phase). The difference between the test and validation datasets is that the test dataset will be used for model selection after it has been completely tuned.
However, there are cases where the validation dataset is not enough to tune the hyperparameters. In such cases, k-fold cross validation is performed on the model.
The input can be seen as follows:
validation_set.shape, training_set.shape
We get the ...
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