Example #1
0
def multinomial(**kwargs):
    """
    Load multinomial NSFW model.

    Returns
    -------
    result : malaya.model.ml.BAYES class
    """
    return classification.multinomial(PATH_NSFW, S3_PATH_NSFW, 'nsfw', label,
                                      **kwargs)
Example #2
0
def multinomial(**kwargs):
    """
    Load multinomial sentiment model.

    Returns
    -------
    result : malaya.model.ml.Bayes class
    """
    return classification.multinomial(
        PATH_SENTIMENT, S3_PATH_SENTIMENT, 'sentiment', label, **kwargs
    )
Example #3
0
def multinomial(**kwargs):
    """
    Load multinomial NSFW model.

    Returns
    -------
    result : malaya.model.ml.BAYES class
    """
    return classification.multinomial(path=PATH_NSFW,
                                      s3_path=S3_PATH_NSFW,
                                      module='nsfw',
                                      label=label,
                                      **kwargs)
Example #4
0
def multinomial(**kwargs):
    """
    Load multinomial emotion model.

    Returns
    -------
    result : malaya.model.ml.MulticlassBayes class
    """
    return classification.multinomial(path=PATH_EMOTION,
                                      s3_path=S3_PATH_EMOTION,
                                      module='emotion',
                                      label=label,
                                      **kwargs)
Example #5
0
def multinomial(**kwargs):
    """
    Load multinomial toxicity model.

    Returns
    -------
    result : malaya.model.ml.MultilabelBayes class
    """
    return classification.multinomial(PATH_TOXIC,
                                      S3_PATH_TOXIC,
                                      'toxicity',
                                      label,
                                      sigmoid=True,
                                      **kwargs)
Example #6
0
def multinomial(**kwargs):
    """
    Load multinomial subjectivity model.

    Parameters
    ----------
    validate: bool, optional (default=True)
        if True, malaya will check model availability and download if not available.

    Returns
    -------
    result : malaya.model.ml.Bayes class
    """
    return classification.multinomial(PATH_SUBJECTIVE, S3_PATH_SUBJECTIVE,
                                      'subjective', label, **kwargs)