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Machine learning algorithms aim at building a model from example inputs in order to make data-driven decisions or predictions.
To illustrate example inputs and outputs, active neurons are colored in the figures.
In Fig. 2, the example inputs produce several such suppressed cells that can be found by their inhibitory input in red with no excitatory input in green.
Table 1 shows example inputs and outputs for TIP.
Information includes the type of input required, a number of example inputs, and a description of the output provided by the query.
Having presented a schematic of the algorithm itself in Figure 1, we provide in Figure 3 a view of example inputs and output MSAs.
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13321_2017_218_MOESM3_ESM.txt Additional file 3. Example input data file.
For example, input prices are assumed to be common across firms.
For example, input from the classroom teacher sometimes changed the outcome of a discussion.
An example input list is given by the first 3 columns of Table 1.
Users can download the example input file for "single" or "multiple" mode and run the tools with default parameters.
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