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In order to carry out our experiments, we split the data set in two parts: train and test.
Samples in each part are used as testing samples in turn and samples in the rest k − 1 parts train the prediction method.
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The intervention was divided into two parts: training and examination.
The CHEMDNER corpus comprises three parts: training (3.5k abstracts), development (3.5k) and testing (3k) datasets.
Normally playback singer identification system is divided into two parts: training phase and testing phase.
The dataset is divided in three parts: training, testing, and validation.
The data were sampled and split into two parts: training with 75% and testing with 25%.
The proposed algorithm is composed of two parts: training process (Algorithm 1) and recognition process (Algorithm 2).
Result is stored in score structure which is divided into two parts (training dataset (80%%) and testing dataset (20 %)).
The execution time of our proposed iris recognition system should be divided into two parts: training and recognition.
This data set is divided into three parts: training, validation and testing.
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CEO of Professional Science Editing for Scientists @ prosciediting.com