Train an ActivePredictionObject[…] to find the predictor for a function, given a set of configurations:

Extract the resulting predictor:

Predict new examples:

Train a prediction object to find the predictor for a function whose domain is defined by an interval:

Extract the predictor:

Predict new examples:

Train a prediction object to find the predictor for the Det function, with the domain defined by a configuration generator:

Extract the predictor:

Predict new examples:

Train a prediction object to find a predictor for the sine function in an interval:

Obtain the list of available object properties:

Obtain the history of explored configurations:

Obtain the predictors trained during active prediction, along with some of their properties:

Obtain the final predictor:

Obtain the method used to choose configurations to add to the training set:

Obtain some other properties:

Display the performances of the predictors trained during active prediction:

Visualize the predictions of the predictor on new examples:

Train a prediction object to find the predictor for a function that computes the color distance between a given color and the red color, with the domain defined by a random color generator:

Obtain the predictor:

Display the performances of the predictors trained during active prediction:

Display the comparison plot of the predictor for a test set:

Define a nontrivial function, with the domain defined by a neighborhood configuration generator:

Train a prediction object to find a predictor for the function, starting with some initial configurations:

Obtain the predictor:

Visualize the predictions of the predictor. It provides a good model of the function in the neighborhood of the initial configurations:

Efficiently train a model to predict the elevation at a specific location:

Sample 1000 random locations to test the quality of the model:

Compare the predicted elevation versus the actual elevation obtained via a server call: