public class MultilayerPerceptronClassificationModel extends PredictionModel<Vector,MultilayerPerceptronClassificationModel> implements scala.Serializable, MLWritable
param: uid uid param: layers array of layer sizes including input and output layers param: weights vector of initial weights for the model that consists of the weights of layers
Modifier and Type | Method and Description |
---|---|
static Params |
clear(Param<?> param) |
MultilayerPerceptronClassificationModel |
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() |
Param<String> |
featuresCol()
Param for features column name.
|
static <T> scala.Option<T> |
get(Param<T> param) |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static String |
getFeaturesCol() |
String |
getFeaturesCol() |
static String |
getLabelCol() |
String |
getLabelCol() |
static <T> T |
getOrDefault(Param<T> param) |
static Param<Object> |
getParam(String paramName) |
static String |
getPredictionCol() |
String |
getPredictionCol() |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(String paramName) |
static boolean |
hasParent() |
static boolean |
isDefined(Param<?> param) |
static boolean |
isSet(Param<?> param) |
static Param<String> |
labelCol() |
Param<String> |
labelCol()
Param for label column name.
|
int[] |
layers() |
static MultilayerPerceptronClassificationModel |
load(String path) |
int |
numFeatures()
Returns the number of features the model was trained on.
|
static Param<?>[] |
params() |
static void |
parent_$eq(Estimator<M> x$1) |
static Estimator<M> |
parent() |
static Param<String> |
predictionCol() |
Param<String> |
predictionCol()
Param for prediction column name.
|
static MLReader<MultilayerPerceptronClassificationModel> |
read() |
static void |
save(String path) |
static <T> Params |
set(Param<T> param,
T value) |
static M |
setFeaturesCol(String value) |
static M |
setParent(Estimator<M> parent) |
static M |
setPredictionCol(String value) |
static String |
toString() |
static Dataset<Row> |
transform(Dataset<?> dataset) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamMap paramMap) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamPair<?> firstParamPair,
ParamPair<?>... otherParamPairs) |
static Dataset<Row> |
transform(Dataset<?> dataset,
ParamPair<?> firstParamPair,
scala.collection.Seq<ParamPair<?>> otherParamPairs) |
static StructType |
transformSchema(StructType schema) |
String |
uid()
An immutable unique ID for the object and its derivatives.
|
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
|
static void |
validateParams() |
Vector |
weights() |
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
setFeaturesCol, setPredictionCol, transform, transformSchema
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
save
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
public static MLReader<MultilayerPerceptronClassificationModel> read()
public static MultilayerPerceptronClassificationModel 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 Dataset<Row> transform(Dataset<?> dataset, ParamPair<?> firstParamPair, scala.collection.Seq<ParamPair<?>> otherParamPairs)
public static Dataset<Row> transform(Dataset<?> dataset, ParamPair<?> firstParamPair, ParamPair<?>... otherParamPairs)
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> labelCol()
public static final String getLabelCol()
public static final Param<String> featuresCol()
public static final String getFeaturesCol()
public static final Param<String> predictionCol()
public static final String getPredictionCol()
public static M setFeaturesCol(String value)
public static M setPredictionCol(String value)
public static StructType transformSchema(StructType schema)
public static void save(String path) throws java.io.IOException
java.io.IOException
public String uid()
Identifiable
uid
in interface Identifiable
public int[] layers()
public Vector weights()
public int numFeatures()
PredictionModel
numFeatures
in class PredictionModel<Vector,MultilayerPerceptronClassificationModel>
public MultilayerPerceptronClassificationModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<MultilayerPerceptronClassificationModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable
public StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
schema
- input schemafitting
- whether this is in fittingfeaturesDataType
- SQL DataType for FeaturesType.
E.g., VectorUDT
for vector features.public Param<String> labelCol()
public String getLabelCol()
public Param<String> featuresCol()
public String getFeaturesCol()
public Param<String> predictionCol()
public String getPredictionCol()