Constructor
new AFTSurvivalRegressionModel()
Extends
Methods
(static) load(path) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
path |
string |
Returns:
(static) read() → {MLReader}
Returns:
- Type
- MLReader
censorCol() → {module:eclairjs/ml/param.Param}
Param for censor column name. The value of this column could be 0 or 1.
If the value is 1, it means the event has occurred i.e. uncensored; otherwise censored.
Returns:
coefficients() → {module:eclairjs/mllib/linalg.Vector}
Returns:
copy(extra) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
extra |
module:eclairjs/ml/param.ParamMap |
Returns:
getCensorCol()
Returns:
{Promise.
getQuantileProbabilities()
Returns:
{Promise.
getQuantilesCol()
Returns:
{Promise.
hasQuantilesCol()
Checks whether the input has quantiles column name.
Returns:
{Promise.
intercept()
Returns:
{Promise.
predict(features) → {Promise.<number>}
Parameters:
| Name | Type | Description |
|---|---|---|
features |
module:eclairjs/mllib/linalg.Vector |
Returns:
- Type
- Promise.<number>
predictQuantiles(features) → {module:eclairjs/mllib/linalg.Vector}
Parameters:
| Name | Type | Description |
|---|---|---|
features |
module:eclairjs/mllib/linalg.Vector |
Returns:
quantileProbabilities() → {DoubleArrayParam}
Param for quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.
Returns:
- Type
- DoubleArrayParam
quantilesCol() → {module:eclairjs/ml/param.Param}
Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.
Returns:
save(path) → {Promise.<Void>}
Saves this ML instance to the input path, a shortcut of `write.save(path)`.
Parameters:
| Name | Type | Description |
|---|---|---|
path |
string |
- Inherited From:
- Source:
Returns:
A Promise that resolves to nothing.
- Type
- Promise.<Void>
scale()
Returns:
{Promise.
setFeaturesCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
string |
Returns:
setPredictionCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
string |
Returns:
setQuantileProbabilities(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
Array.<number> |
Returns:
setQuantilesCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}
Parameters:
| Name | Type | Description |
|---|---|---|
value |
string |
Returns:
transform(dataset) → {module:eclairjs/sql.Dataset}
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
module:eclairjs/sql.Dataset |
Returns:
transformSchema(schema) → {module:eclairjs/sql/types.StructType}
Parameters:
| Name | Type | Description |
|---|---|---|
schema |
module:eclairjs/sql/types.StructType |
Returns:
uid()
An immutable unique ID for the object and its derivatives.
Returns:
{Promise.
validateAndTransformSchema(schema, fitting) → {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 | input schema |
fitting |
boolean | whether this is in fitting or prediction |
Returns:
write() → {MLWriter}
- Overrides:
- Source:
Returns:
- Type
- MLWriter