def __init__(self):
super(HasMetrics, self).__init__()
self.metrics = Param(self, "metrics", "Keras metrics")
def __init__(self):
super(HasNumberOfWorkers, self).__init__()
self.num_workers = Param(self, "num_workers", "number of workers")
self._setDefault(num_workers=8)
def __init__(self):
super(HasKerasOptimizerConfig, self).__init__()
self.optimizer_config = Param(self, "optimizer_config",
"Serialized Keras optimizer properties")
self._setDefault(optimizer_config=None)
def __init__(self):
super(HasValidationSplit, self).__init__()
self.validation_split = Param(self, "validation_split",
"validation split percentage")
self._setDefault(validation_split=0.1)
def __init__(self):
super(HasVerbosity, self).__init__()
self.verbose = Param(self, "verbose", "Stdout verbosity")
self._setDefault(verbose=0)
def __init__(self):
super(HasBatchSize, self).__init__()
self.batch_size = Param(self, "batch_size", "Batch size")
self._setDefault(batch_size=32)
def __init__(self):
super(HasEpochs, self).__init__()
self.epochs = Param(self, "epochs", "Number of epochs to train")
self._setDefault(epochs=10)
def __init__(self, inputCol=None, outputCol=None, alpha=None):
super(BoxCoxTransformer, self).__init__()
self.alpha = Param(self, "alpha", 0)
self._setDefault(alpha=0)
kwargs = self.__init__._input_kwargs
self.setParams(**kwargs)
