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Object org.apache.spark.mllib.evaluation.RegressionMetrics
public class RegressionMetrics
:: Experimental :: Evaluator for regression.
param: predictionAndObservations an RDD of (prediction, observation) pairs.
Constructor Summary | |
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RegressionMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndObservations)
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Method Summary | |
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double |
explainedVariance()
Returns the explained variance regression score. |
double |
meanAbsoluteError()
Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss. |
double |
meanSquaredError()
Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss. |
double |
r2()
Returns R^2^, the coefficient of determination. |
double |
rootMeanSquaredError()
Returns the root mean squared error, which is defined as the square root of the mean squared error. |
Methods inherited from class Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface org.apache.spark.Logging |
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initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning |
Constructor Detail |
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public RegressionMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndObservations)
Method Detail |
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public double explainedVariance()
http://en.wikipedia.org/wiki/Explained_variation
public double meanAbsoluteError()
public double meanSquaredError()
public double rootMeanSquaredError()
public double r2()
http://en.wikipedia.org/wiki/Coefficient_of_determination
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