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Seventy-four stations from the long-period Australia-wide AusLAMP (Australian Lithospheric Architecture Magnetotelluric Project) dataset were used to image the electrical resistivity beneath the Neoproterozoic Ikara Flinders Ranges and adjacent Palaeo-Mesoproterozoic Curnamona Province.
To address both problems, we optimized the parameters for every method with a grid search (Supplementary Note 2) and used an approach akin to cross-validation where the optimal parameter settings from one dataset were used to assess the performance of a method on another dataset (Fig. 1c).
Four publicly available email datasets and one publicly available phish URL dataset were used to evaluate phishGILLNET.
In [46], personality annotations in a video blog dataset were used to transfer information to the training models obtained from the ELEA dataset.
In this algorithm, some of retinal images in dataset were used to create a template and the correlation between each image and template is computed.
We use the training dataset as input to train the SVM model, then the testing dataset were used to examine the model.
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The dictionary of useful decoys (DUD) [16] dataset was used to perform virtual screening (VS) studies.
The MovieLens dataset is used to compare different clustering algorithms.
Once the models were trained, the validation dataset was used to select the best performing model and then the test dataset was used to assess its accuracy.
An experimental dataset was used to perform the validation and analysis.
The dataset was used to develop virtual binding pockets for accommodating HLA-II specific sHLA-II specific
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