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From the collected data, a binary classification problem is created.
For our data, a binary classification was performed using a non-linear SVC with a radial basis function (RBF) kernel.
Based on the data, a binary logit (BL) model was developed to identify what and how the factors affect the selective preference of overpass.
Based on these and other data, a binary decision model has been proposed to explain the transition between regulatory states of cells [ 38].
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Level 0 data is a binary image data that is constructed from the compressed and fragmented packet data.
For analyses drawing on only the CHETS Wales 2 data or using both the data sets a binary variable ("ever used e-cigarettes") was used.
There is excellent agreement between the results of our methodology and experimental data for a pure component and Monte Carlo simulation data for a binary mixture.
The information lost when transforming continuous data into a binary response measure translates into a loss of power to detect differences between treatments in mixed treatment comparison models.
This paper first introduces a binary-block embedding (BBE) method to embed secret data in a binary image.
The problem involves calculating of the liquid vapour equilibrium data of a binary mixture with a homogeneous maximum azeotrope.
Experimental data of a binary system distillated in a falling film molecular distillator are used for the validation of the developed procedure.
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