blocking

class deduplipy.blocking.Blocking(col_names, rules=None, recall=1.0, save_intermediate_steps=False)

Bases: sklearn.base.BaseEstimator

fit(X, y)

Fit Blocking instance on data

Args:

X: array containing pairs y: array containing whether pairs are a match or not

Returns:

fitted instance

transform(X)

Applies blocking rules on new data

Args:

X: Pandas dataframe containing data on which blocking rules should be applied

Returns:

Pandas dataframe containing blocking rules applied on new data

deduplipy.blocking.greedy_set_cover(subsets, parent_set, recall=1.0)

Greedy set cover algorithm, stops when recall threshold is reached

Args:

subsets: subsets that should cover the parent_set parent_set: parent_set that should be covered by subsets recall: minimum recall to reach

Returns:

list containing selection of rules that collectively span the parent_set