The MLFeature class is an abstract base class representing input and output features used in making predictions. All predictors accept one or more features, which are then provided to the model to make predictions.
Creating a Feature
NatML provides implicit conversions from common data types into MLFeature instances:
From an Array
// With a `float` array
float array =...;
// Create a feature
MLFeature feature = array;
// Then make a prediction
// This works too
NatML provides an implicit conversion from a float to an MLArrayFeature.
When this conversion is used, the created feature will have no shape information.