public class AFTSurvivalRegressionModel extends Model<AFTSurvivalRegressionModel> implements MLWritable
AFTSurvivalRegression
.Modifier and Type | Method and Description |
---|---|
static Param<String> |
censorCol() |
Param<String> |
censorCol()
Param for censor column name.
|
static Params |
clear(Param<?> param) |
Vector |
coefficients() |
AFTSurvivalRegressionModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static String |
explainParam(Param<?> param) |
static String |
explainParams() |
static ParamMap |
extractParamMap() |
static ParamMap |
extractParamMap(ParamMap extra) |
static Param<String> |
featuresCol() |
static BooleanParam |
fitIntercept() |
static <T> scala.Option<T> |
get(Param<T> param) |
static String |
getCensorCol() |
String |
getCensorCol() |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static String |
getFeaturesCol() |
static boolean |
getFitIntercept() |
static String |
getLabelCol() |
static int |
getMaxIter() |
static <T> T |
getOrDefault(Param<T> param) |
static Param<Object> |
getParam(String paramName) |
static String |
getPredictionCol() |
static double[] |
getQuantileProbabilities() |
double[] |
getQuantileProbabilities() |
static String |
getQuantilesCol() |
String |
getQuantilesCol() |
static double |
getTol() |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(String paramName) |
static boolean |
hasParent() |
boolean |
hasQuantilesCol()
Checks whether the input has quantiles column name.
|
double |
intercept() |
static boolean |
isDefined(Param<?> param) |
static boolean |
isSet(Param<?> param) |
static Param<String> |
labelCol() |
static AFTSurvivalRegressionModel |
load(String path) |
static IntParam |
maxIter() |
static Param<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
double |
predict(Vector features) |
static Param<String> |
predictionCol() |
Vector |
predictQuantiles(Vector features) |
static DoubleArrayParam |
quantileProbabilities() |
DoubleArrayParam |
quantileProbabilities()
Param for quantile probabilities array.
|
static Param<String> |
quantilesCol() |
Param<String> |
quantilesCol()
Param for quantiles column name.
|
static MLReader<AFTSurvivalRegressionModel> |
read() |
static void |
save(String path) |
double |
scale() |
static <T> Params |
set(Param<T> param,
T value) |
AFTSurvivalRegressionModel |
setFeaturesCol(String value) |
static M |
setParent(Estimator<M> parent) |
AFTSurvivalRegressionModel |
setPredictionCol(String value) |
AFTSurvivalRegressionModel |
setQuantileProbabilities(double[] value) |
AFTSurvivalRegressionModel |
setQuantilesCol(String value) |
static DoubleParam |
tol() |
static String |
toString() |
Dataset<Row> |
transform(Dataset<?> dataset)
Transforms the input dataset.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting)
Validates and transforms the input schema with the provided param map.
|
static void |
validateParams() |
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams
toString
save
public static MLReader<AFTSurvivalRegressionModel> read()
public static AFTSurvivalRegressionModel load(String path)
public static String toString()
public static Param<?>[] params()
public static void validateParams()
public static String explainParam(Param<?> param)
public static String explainParams()
public static final boolean isSet(Param<?> param)
public static final boolean isDefined(Param<?> param)
public static boolean hasParam(String paramName)
public static Param<Object> getParam(String paramName)
public static final <T> scala.Option<T> get(Param<T> param)
public static final <T> T getOrDefault(Param<T> param)
public static final <T> scala.Option<T> getDefault(Param<T> param)
public static final <T> boolean hasDefault(Param<T> param)
public static final ParamMap extractParamMap()
public static Estimator<M> parent()
public static void parent_$eq(Estimator<M> x$1)
public static M setParent(Estimator<M> parent)
public static boolean hasParent()
public static final Param<String> featuresCol()
public static final String getFeaturesCol()
public static final Param<String> labelCol()
public static final String getLabelCol()
public static final Param<String> predictionCol()
public static final String getPredictionCol()
public static final IntParam maxIter()
public static final int getMaxIter()
public static final DoubleParam tol()
public static final double getTol()
public static final BooleanParam fitIntercept()
public static final boolean getFitIntercept()
public static final Param<String> censorCol()
public static String getCensorCol()
public static final DoubleArrayParam quantileProbabilities()
public static double[] getQuantileProbabilities()
public static final Param<String> quantilesCol()
public static String getQuantilesCol()
public static void save(String path) throws java.io.IOException
java.io.IOException
public String uid()
Identifiable
uid
in interface Identifiable
public Vector coefficients()
public double intercept()
public double scale()
public AFTSurvivalRegressionModel setFeaturesCol(String value)
public AFTSurvivalRegressionModel setPredictionCol(String value)
public AFTSurvivalRegressionModel setQuantileProbabilities(double[] value)
public AFTSurvivalRegressionModel setQuantilesCol(String value)
public double predict(Vector features)
public Dataset<Row> transform(Dataset<?> dataset)
Transformer
transform
in class Transformer
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
Check transform validity and derive the output schema from the input schema.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public AFTSurvivalRegressionModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<AFTSurvivalRegressionModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public Param<String> censorCol()
public String getCensorCol()
public DoubleArrayParam quantileProbabilities()
public double[] getQuantileProbabilities()
public Param<String> quantilesCol()
public String getQuantilesCol()
public boolean hasQuantilesCol()
public StructType validateAndTransformSchema(StructType schema, boolean fitting)
schema
- input schemafitting
- whether this is in fitting or prediction