public class MulticlassClassificationEvaluator extends Evaluator implements HasPredictionCol, HasLabelCol, DefaultParamsWritable
| Constructor and Description |
|---|
MulticlassClassificationEvaluator() |
MulticlassClassificationEvaluator(String uid) |
| Modifier and Type | Method and Description |
|---|---|
static Params |
clear(Param<?> param) |
MulticlassClassificationEvaluator |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
double |
evaluate(Dataset<?> dataset)
Evaluates model output and returns a scalar metric.
|
static String |
explainParam(Param<?> param) |
static String |
explainParams() |
static ParamMap |
extractParamMap() |
static ParamMap |
extractParamMap(ParamMap extra) |
static <T> scala.Option<T> |
get(Param<T> param) |
static <T> scala.Option<T> |
getDefault(Param<T> param) |
static String |
getLabelCol() |
String |
getMetricName() |
static <T> T |
getOrDefault(Param<T> param) |
static Param<Object> |
getParam(String paramName) |
static String |
getPredictionCol() |
static <T> boolean |
hasDefault(Param<T> param) |
static boolean |
hasParam(String paramName) |
static boolean |
isDefined(Param<?> param) |
boolean |
isLargerBetter()
Indicates whether the metric returned by
evaluate should be maximized (true, default)
or minimized (false). |
static boolean |
isSet(Param<?> param) |
static Param<String> |
labelCol() |
static MulticlassClassificationEvaluator |
load(String path) |
Param<String> |
metricName()
param for metric name in evaluation (supports
"f1" (default), "weightedPrecision",
"weightedRecall", "accuracy") |
static Param<?>[] |
params() |
static Param<String> |
predictionCol() |
static void |
save(String path) |
static <T> Params |
set(Param<T> param,
T value) |
MulticlassClassificationEvaluator |
setLabelCol(String value) |
MulticlassClassificationEvaluator |
setMetricName(String value) |
MulticlassClassificationEvaluator |
setPredictionCol(String value) |
static String |
toString() |
String |
uid()
An immutable unique ID for the object and its derivatives.
|
static MLWriter |
write() |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetPredictionCol, predictionColgetLabelCol, labelColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringwritesavepublic MulticlassClassificationEvaluator(String uid)
public MulticlassClassificationEvaluator()
public static MulticlassClassificationEvaluator load(String path)
public static String toString()
public static Param<?>[] params()
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 final Param<String> predictionCol()
public static final String getPredictionCol()
public static final Param<String> labelCol()
public static final String getLabelCol()
public static void save(String path)
throws java.io.IOException
java.io.IOExceptionpublic static MLWriter write()
public String uid()
Identifiableuid in interface Identifiablepublic Param<String> metricName()
"f1" (default), "weightedPrecision",
"weightedRecall", "accuracy")public String getMetricName()
public MulticlassClassificationEvaluator setMetricName(String value)
public MulticlassClassificationEvaluator setPredictionCol(String value)
public MulticlassClassificationEvaluator setLabelCol(String value)
public double evaluate(Dataset<?> dataset)
EvaluatorisLargerBetter specifies whether larger values are better.
public boolean isLargerBetter()
Evaluatorevaluate should be maximized (true, default)
or minimized (false).
A given evaluator may support multiple metrics which may be maximized or minimized.isLargerBetter in class Evaluatorpublic MulticlassClassificationEvaluator copy(ParamMap extra)
ParamsdefaultCopy().