org.apache.spark.mllib.regression
IsotonicRegressionModel
Related Docs:
object IsotonicRegressionModel
| package regression
org.apache.spark.mllib.regression
A Java-friendly constructor that takes two Iterable parameters and one Boolean parameter.
A Java-friendly constructor that takes two Iterable parameters and one Boolean parameter.
Array of boundaries for which predictions are known. Boundaries must be sorted in increasing order.
Array of predictions associated to the boundaries at the same index. Results of isotonic regression and therefore monotone.
indicates whether this is isotonic or antitonic.
Array of boundaries for which predictions are known.
Array of boundaries for which predictions are known. Boundaries must be sorted in increasing order.
Current version of model save/load format.
Current version of model save/load format.
indicates whether this is isotonic or antitonic.
indicates whether this is isotonic or antitonic.
Predict a single label.
Predict a single label. Using a piecewise linear function.
Feature to be labeled.
Predicted label. 1) If testData exactly matches a boundary then associated prediction is returned. In case there are multiple predictions with the same boundary then one of them is returned. Which one is undefined (same as java.util.Arrays.binarySearch). 2) If testData is lower or higher than all boundaries then first or last prediction is returned respectively. In case there are multiple predictions with the same boundary then the lowest or highest is returned respectively. 3) If testData falls between two values in boundary array then prediction is treated as piecewise linear function and interpolated value is returned. In case there are multiple values with the same boundary then the same rules as in 2) are used.
Predict labels for provided features.
Predict labels for provided features. Using a piecewise linear function.
Features to be labeled.
Predicted labels.
Predict labels for provided features.
Predict labels for provided features. Using a piecewise linear function.
Features to be labeled.
Predicted labels.
Array of predictions associated to the boundaries at the same index.
Array of predictions associated to the boundaries at the same index. Results of isotonic regression and therefore monotone.
Save this model to the given path.
Save this model to the given path.
This saves:
The model may be loaded using Loader.load.
Spark context used to save model data.
Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.
Regression model for isotonic regression.