Constructor
new RandomForestRegressionModel()
Extends
Methods
(static) load(path) → {module:eclairjs/ml/regression.RandomForestRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
path |
string |
Returns:
(static) read() → {module:eclairjs/ml/util.MLReader}
Returns:
copy(extra) → {module:eclairjs/ml/regression.RandomForestRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
extra |
module:eclairjs/ml/param.ParamMap |
- Overrides:
- Source:
Returns:
featureImportances() → {module:eclairjs/mllib/linalg.Vector}
Estimate of the importance of each feature.
This generalizes the idea of "Gini" importance to other losses, following the explanation of Gini importance
from "Random Forests" documentation by Leo Breiman and Adele Cutler, and following the implementation from scikit-learn.
This feature importance is calculated as follows: - Average over trees: - importance(feature j) = sum (over nodes which split on feature j)
of the gain, where gain is scaled by the number of instances passing through node - Normalize importances for
tree based on total number of training instances used to build tree. - Normalize feature importance vector to sum to 1.
Returns:
featuresCol() → {module:eclairjs/ml/param.Param}
Param for features column name.
- Overrides:
- Source:
Returns:
getFeaturesCol() → {string}
- Overrides:
- Source:
Returns:
- Type
- string
getLabelCol() → {string}
- Overrides:
- Source:
Returns:
- Type
- string
getPredictionCol() → {string}
- Overrides:
- Source:
Returns:
- Type
- string
hasParent() → {boolean}
- Inherited From:
- Source:
Returns:
- Type
- boolean
labelCol() → {module:eclairjs/ml/param.Param}
Param for label column name.
- Overrides:
- Source:
Returns:
numFeatures() → {integer}
- Inherited From:
- Source:
Returns:
- Type
- integer
parent() → {module:eclairjs/ml.Estimator}
- Inherited From:
- Source:
Returns:
predictionCol() → {module:eclairjs/ml/param.Param}
Param for prediction column name.
- Overrides:
- Source:
Returns:
setFeaturesCol(value) → {object}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
string |
- Inherited From:
- Source:
Returns:
- Type
- object
setParent(parent) → {object}
Sets the parent of this model.
Parameters:
| Name | Type | Description |
|---|---|---|
parent |
module:eclairjs/ml.Estimator |
- Inherited From:
- Source:
Returns:
- Type
- object
setPredictionCol(value) → {object}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
string |
- Inherited From:
- Source:
Returns:
- Type
- object
toDebugString() → {string}
Returns:
- Type
- string
toString() → {string}
Returns:
- Type
- string
transform(dataset) → {module:eclairjs/sql.Dataset}
Transforms dataset by reading from featuresCol, calling [[predict()]], and storing
the predictions as a new column predictionCol.
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
module:eclairjs/sql.Dataset | input dataset |
- Inherited From:
- Source:
Returns:
transformed dataset with [[predictionCol]] of type [[Double]]
transformSchema(schema) → {module:eclairjs/sql/types.StructType}
Parameters:
| Name | Type | Description |
|---|---|---|
schema |
module:eclairjs/sql/types.StructType |
- Inherited From:
- Source:
Returns:
trees() → {Array.<DecisionTreeModel>}
Returns:
- Type
- Array.<DecisionTreeModel>
treeWeights() → {Array.<float>}
Returns:
- Type
- Array.<float>
uid() → {string}
An immutable unique ID for the object and its derivatives.
Returns:
- Type
- string
validateAndTransformSchema(schema, fitting, featuresDataType) → {module:eclairjs/sql/types.StructType}
Validates and transforms the input schema with the provided param map.
Parameters:
| Name | Type | Description |
|---|---|---|
schema |
module:eclairjs/sql/types.StructType | |
fitting |
boolean | whether this is in fitting |
featuresDataType |
module:eclairjs/sql/types.DataType | SQL DataType for FeaturesType. E.g., module:eclairjs/sql/types.VectorUDTfor vector features |
- Overrides:
- Source: