Test Result : LinearRegressionSuite

0 failures (±0) , 1 skipped (±0)
32 tests (±0)
Took 3 min 0 sec.

All Tests

Test nameDurationStatus
export test data into CSV format-1 msSkipped
huber loss model match squared error for large epsilon1.3 secPassed
linear regression (huber loss) with intercept with L2 regularization1.6 secPassed
linear regression (huber loss) with intercept without regularization2.6 secPassed
linear regression (huber loss) without intercept with L2 regularization1.5 secPassed
linear regression (huber loss) without intercept without regularization1.5 secPassed
linear regression handles singular matrices3 secPassed
linear regression model testset evaluation summary3.8 secPassed
linear regression model training summary4.8 secPassed
linear regression model with constant label4.7 secPassed
linear regression model with l-bfgs with big feature datasets1.7 secPassed
linear regression summary with weighted samples and intercept by normal solver1 secPassed
linear regression summary with weighted samples and w/o intercept by normal solver0.57 secPassed
linear regression with intercept with ElasticNet regularization6.3 secPassed
linear regression with intercept with L1 regularization9.4 secPassed
linear regression with intercept with L2 regularization10 secPassed
linear regression with intercept without regularization7.3 secPassed
linear regression with l-bfgs when training is not needed3.6 secPassed
linear regression with weighted samples1 min 0 secPassed
linear regression without intercept with ElasticNet regularization5.9 secPassed
linear regression without intercept with L1 regularization9.4 secPassed
linear regression without intercept with L2 regularization6.8 secPassed
linear regression without intercept without regularization12 secPassed
linear regression: can transform data with LinearRegressionModel0.79 secPassed
linear regression: default params0.88 secPassed
linear regression: illegal params8 msPassed
params1 msPassed
pmml export3.4 secPassed
prediction on single instance0.72 secPassed
read/write2.3 secPassed
regularized linear regression through origin with constant label1 secPassed
should support all NumericType labels and weights, and not support other types10 secPassed