new IsotonicRegressionModel(boundaries, predictions, isotonic)
A Java-friendly constructor that takes two Iterable parameters and one Boolean parameter.
Parameters:
Name | Type | Description |
---|---|---|
boundaries |
Iterable | |
predictions |
Iterable | |
isotonic |
boolean |
Methods
predict(testData) → {module:eclairjs/rdd.RDD|Promise.<number>}
Predict labels for provided features, or single label..
Using a piecewise linear function.
Parameters:
Name | Type | Description |
---|---|---|
testData |
module:eclairjs/rdd.RDD | DoubleRDD | float | Features to be labeled, if float. 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. |
Returns:
Predicted labels or label.
- Type
- module:eclairjs/rdd.RDD | Promise.<number>
save(sc, path) → {Promise.<Void>}
Parameters:
Name | Type | Description |
---|---|---|
sc |
module:eclairjs.SparkContext | |
path |
string |
Returns:
A Promise that resolves to nothing.
- Type
- Promise.<Void>