Constructor
new LinearRegressionTrainingSummary()
Extends
Methods
coefficientStandardErrors() → {Array.<float>}
Standard error of estimated coefficients and intercept.
- Inherited From:
- Source:
Returns:
- Type
- Array.<float>
devianceResiduals() → {Array.<float>}
The weighted residuals, the usual residuals rescaled by the square root of the instance weights.
- Inherited From:
- Source:
Returns:
- Type
- Array.<float>
explainedVariance() → {float}
- Inherited From:
- Source:
Returns:
- Type
- float
featuresCol() → {string}
Returns:
- Type
- string
labelCol() → {string}
- Inherited From:
- Source:
Returns:
- Type
- string
meanAbsoluteError() → {float}
Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss.
Note: This ignores instance weights (setting all to 1.0) from LinearRegression.weightCol. This will change in later Spark versions.
- Inherited From:
- Source:
Returns:
- Type
- float
meanSquaredError() → {float}
Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss.
Note: This ignores instance weights (setting all to 1.0) from LinearRegression.weightCol. This will change in later Spark versions.
- Inherited From:
- Source:
Returns:
- Type
- float
model() → {module:eclairjs/ml/regression.LinearRegressionModel}
- Inherited From:
- Source:
Returns:
numInstances() → {integer}
Number of instances in DataFrame predictions
- Inherited From:
- Source:
Returns:
- Type
- integer
objectiveHistory() → {Array.<float>}
Returns:
- Type
- Array.<float>
predictionCol() → {string}
- Inherited From:
- Source:
Returns:
- Type
- string
predictions() → {module:eclairjs/sql.DataFrame}
- Inherited From:
- Source:
Returns:
- Type
- module:eclairjs/sql.DataFrame
pValues() → {Array.<float>}
Two-sided p-value of estimated coefficients and intercept.
- Inherited From:
- Source:
Returns:
- Type
- Array.<float>
r2() → {float}
Returns R^2^, the coefficient of determination. Reference: http://en.wikipedia.org/wiki/Coefficient_of_determination
Note: This ignores instance weights (setting all to 1.0) from LinearRegression.weightCol. This will change in later Spark versions.
- Inherited From:
- Source:
Returns:
- Type
- float
residuals() → {module:eclairjs/sql.DataFrame}
Residuals (label - predicted value)
- Inherited From:
- Source:
Returns:
- Type
- module:eclairjs/sql.DataFrame
rootMeanSquaredError() → {float}
Returns the root mean squared error, which is defined as the square root of the mean squared error.
Note: This ignores instance weights (setting all to 1.0) from LinearRegression.weightCol. This will change in later Spark versions.
- Inherited From:
- Source:
Returns:
- Type
- float
totalIterations() → {integer}
Returns:
- Type
- integer
tValues() → {Array.<float>}
T-statistic of estimated coefficients and intercept.
- Inherited From:
- Source:
Returns:
- Type
- Array.<float>