public class Word2VecModel extends Model<Word2VecModel> implements Word2VecBase, MLWritable
Word2Vec
.Modifier and Type | Class and Description |
---|---|
static class |
Word2VecModel.Word2VecModelWriter$ |
Modifier and Type | Method and Description |
---|---|
Word2VecModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Dataset<Row> |
findSynonyms(String word,
int num)
Find "num" number of words closest in similarity to the given word, not
including the word itself.
|
Dataset<Row> |
findSynonyms(Vector vec,
int num)
Find "num" number of words whose vector representation is most similar to the supplied vector.
|
scala.Tuple2<String,Object>[] |
findSynonymsArray(String word,
int num)
Find "num" number of words closest in similarity to the given word, not
including the word itself.
|
scala.Tuple2<String,Object>[] |
findSynonymsArray(Vector vec,
int num)
Find "num" number of words whose vector representation is most similar to the supplied vector.
|
Dataset<Row> |
getVectors()
Returns a dataframe with two fields, "word" and "vector", with "word" being a String and
and the vector the DenseVector that it is mapped to.
|
static Word2VecModel |
load(String path) |
static MLReader<Word2VecModel> |
read() |
Word2VecModel |
setInputCol(String value) |
Word2VecModel |
setOutputCol(String value) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transform a sentence column to a vector column to represent the whole sentence.
|
StructType |
transformSchema(StructType schema)
:: DeveloperApi ::
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
MLWriter |
write()
Returns an
MLWriter instance for this ML instance. |
transform, transform, transform
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getMaxSentenceLength, getMinCount, getNumPartitions, getVectorSize, getWindowSize, maxSentenceLength, minCount, numPartitions, validateAndTransformSchema, vectorSize, windowSize
getInputCol, inputCol
getOutputCol, outputCol
getMaxIter, maxIter
getStepSize, stepSize
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString
save
initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public static MLReader<Word2VecModel> read()
public static Word2VecModel load(String path)
public String uid()
Identifiable
uid
in interface Identifiable
public Dataset<Row> getVectors()
public Dataset<Row> findSynonyms(String word, int num)
word
- (undocumented)num
- (undocumented)public Dataset<Row> findSynonyms(Vector vec, int num)
vec
- (undocumented)num
- (undocumented)public scala.Tuple2<String,Object>[] findSynonymsArray(Vector vec, int num)
vec
- (undocumented)num
- (undocumented)public scala.Tuple2<String,Object>[] findSynonymsArray(String word, int num)
word
- (undocumented)num
- (undocumented)public Word2VecModel setInputCol(String value)
public Word2VecModel setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
transform
in class Transformer
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
Check transform validity and derive the output schema from the input schema.
We check validity for interactions between parameters during transformSchema
and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public Word2VecModel copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Model<Word2VecModel>
extra
- (undocumented)public MLWriter write()
MLWritable
MLWriter
instance for this ML instance.write
in interface MLWritable