public class PCAModel extends Model<PCAModel> implements PCAParams, MLWritable
PCA. Transforms vectors to a lower dimensional space.
param: pc A principal components Matrix. Each column is one principal component. param: explainedVariance A vector of proportions of variance explained by each principal component.
| Modifier and Type | Method and Description |
|---|---|
PCAModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
DenseVector |
explainedVariance() |
static PCAModel |
load(String path) |
DenseMatrix |
pc() |
static MLReader<PCAModel> |
read() |
PCAModel |
setInputCol(String value) |
PCAModel |
setOutputCol(String value) |
Dataset<Row> |
transform(Dataset<?> dataset)
Transform a vector by computed Principal Components.
|
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, transformequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetK, k, validateAndTransformSchemagetInputCol, inputColgetOutputCol, outputColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringsaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic static PCAModel load(String path)
public String uid()
Identifiableuid in interface Identifiablepublic DenseMatrix pc()
public DenseVector explainedVariance()
public PCAModel setInputCol(String value)
public PCAModel setOutputCol(String value)
public Dataset<Row> transform(Dataset<?> dataset)
transform in class Transformerdataset - (undocumented)PCA.fit().public StructType transformSchema(StructType schema)
PipelineStageCheck 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 PipelineStageschema - (undocumented)public PCAModel copy(ParamMap extra)
ParamsdefaultCopy().public MLWriter write()
MLWritableMLWriter instance for this ML instance.write in interface MLWritable