AuDoLab.subclasses.one_class_svm

class AuDoLab.subclasses.one_class_svm.One_Class_SVM

Bases: object

static choose_classifier(df, classifier, i)

Returns dataframe where documents that are classified to target class have 1, otherwise, 0

Args:

df (pd.Dataframe): dataframe of target documents

classifier (list): list of all possible o-svm classifiers

i (int): index of which classifier is chosen/preferred

Returns:

pd.dataframe: documents that are classified as belonging to target

static classification(training, predicting, nus, quality_train=0.85, min_pred=0.05, max_pred=0.2, gamma='auto', kernel='rbf')

Returns the classifiers that fullfill the required conditions.

Args:

training (DataFrame): training dataset of preprocessed documents

predicting (DataFrame): target dataset of preprccessed documents

nus (list of floats): hyperparameters over which are looped. For

each nu the classifier is trained

quality_train (float, optional): percentage of training data that

seems to belong to target class. Default: 0.85. Defaults to 0.85.

min_pred (float, optional): percentage of target data that has to be

at least classified as belonging to target class for classifier to be considered. Default: 0.0. Defaults to 0.05.

max_pred (float, optional): percentage of target class that is

maximally allowed to be classified as belonging to

target class for classifier to be considered.. Defaults to 0.2.

gamma (str, optional): Hyperparamter of O-SVM. Defaults to “auto”.

kernel (str, optional): Kernel function used in O_SVM. Defaults to

“rbf”.

Returns:

pd.DataFrame: DataFrame with stored classifiers that fulfill

conditions

AuDoLab.subclasses.one_class_svm.warn(*args, **kwargs)