Methods
coefficientStandardErrors() → {Promise.<Array.<number>>}
Standard error of estimated coefficients and intercept.
Returns:
- Type
- Promise.<Array.<number>>
devianceResiduals() → {Promise.<Array.<number>>}
The weighted residuals, the usual residuals rescaled by the square root of the instance weights.
Returns:
- Type
- Promise.<Array.<number>>
explainedVariance() → {Promise.<number>}
Returns:
- Type
- Promise.<number>
labelCol() → {Promise.<string>}
Returns:
- Type
- Promise.<string>
meanAbsoluteError() → {Promise.<number>}
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.
Returns:
- Type
- Promise.<number>
meanSquaredError() → {Promise.<number>}
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.
Returns:
- Type
- Promise.<number>
model() → {module:eclairjs/ml/regression.LinearRegressionModel}
Returns:
numInstances() → {Promise.<number>}
Number of instances in DataFrame predictions
Returns:
- Type
- Promise.<number>
predictionCol() → {Promise.<string>}
Returns:
- Type
- Promise.<string>
predictions() → {module:eclairjs/sql.DataFrame}
Returns:
pValues() → {Promise.<Array.<number>>}
Two-sided p-value of estimated coefficients and intercept.
Returns:
- Type
- Promise.<Array.<number>>
r2() → {Promise.<number>}
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.
Returns:
- Type
- Promise.<number>
residuals() → {module:eclairjs/sql.DataFrame}
Residuals (label - predicted value)
Returns:
rootMeanSquaredError() → {Promise.<number>}
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.
Returns:
- Type
- Promise.<number>
tValues() → {Promise.<Array.<number>>}
T-statistic of estimated coefficients and intercept.
Returns:
- Type
- Promise.<Array.<number>>