@@ -51,9 +51,9 @@ class AutoFeaturizer(DFTransformer, LoggableMixin):
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from this file instead of featurizing. If this file does not exist,
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AutoFeaturizer will featurize normally, then save the features to a
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new file. Only features (not featurizer input objects) will be saved
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- preset (str): "best " or "robust " or "all" . Determines by preset the
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- featurizers that should be applied. See the Featurizer sets for
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- specifics of best/robust/all . Default is "best ". Incompatible with
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+ preset (str): "express " or "heavy " or "debug" or "all . Determines by
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+ preset the featurizers that should be applied. See the Featurizer
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+ sets for specifics of each . Default is "express ". Incompatible with
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the featurizers arg.
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featurizers (dict): Use this option if you want to manually specify
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the featurizers to use. Keys are the featurizer types you want
@@ -118,15 +118,16 @@ def __init__(self, cache_src=None, preset=None, featurizers=None,
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if featurizers and preset :
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raise AutomatminerError ("Featurizers and preset were both set. "
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- "Please either use a preset ('best', 'all',"
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- " 'robust') or set featurizers manually." )
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+ "Please either use a preset ('express', "
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+ "'all', 'debug', 'heavy') or set "
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+ "featurizers manually." )
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if not featurizers and not preset :
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raise AutomatminerError ("Please specify set(s) of featurizers to "
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"use either through the featurizers"
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"argument or through the preset argument." )
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self .cache_src = cache_src
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- self .preset = "best " if preset is None else preset
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+ self .preset = "express " if preset is None else preset
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self ._logger = self .get_logger (logger )
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self .featurizers = featurizers
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self .exclude = exclude if exclude else []
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