NEURECO TABULAR
TABULAR REGRESSION
This template of tabular solution is used to create neural network models where the outputs are values at the points of some continuous process (physical data, measured data…). NeurEco will create a regression predictive model that approximate the underlying process by a function (f) from inputs (X) to the output variable (Y).
TABULAR CLASSIFICATION
This template of tabular solution is used to create neural network models performing supervised predictive classification. It is used when the output variable is a category and the model attempts to classify the data, that is draw conclusions from observations and predict categorical class labels.
TABULAR COMPRESSION
This template of tabular solution is used to create neural network models where the targets are the same as the inputs. These models will compress the input into a lower dimension representation and then reconstruct the output from this representation. The representation is a compact summary or compression of the input. This solution is a powerful tool to reduce dimensionality without losing the physical meaning of the inputs.