DedupliPy
v0.8

Contents:

  • Installation
  • Tutorial
  • API Reference
DedupliPy
  • Index
  • Edit on GitHub

Index

A | B | C | D | F | G | H | L | M | N | P | S | T

A

  • adjusted_partial_ratio() (in module deduplipy.string_metrics)
  • adjusted_ratio() (in module deduplipy.string_metrics)
  • adjusted_token_set_ratio() (in module deduplipy.string_metrics)
  • adjusted_token_sort_ratio() (in module deduplipy.string_metrics)

B

  • Blocking (class in deduplipy.blocking)

C

  • ClassifierPipeline (class in deduplipy.classifier_pipeline)

D

  • deduplipy.blocking
    • module
  • deduplipy.classifier_pipeline
    • module
  • deduplipy.clustering
    • module
  • deduplipy.datasets
    • module
  • deduplipy.sampling
    • module
  • deduplipy.string_metrics
    • module

F

  • fill_missing_links() (in module deduplipy.clustering)
  • fit() (deduplipy.blocking.Blocking method)
    • (deduplipy.classifier_pipeline.ClassifierPipeline method)

G

  • greedy_set_cover() (in module deduplipy.blocking)

H

  • hierarchical_clustering() (in module deduplipy.clustering)

L

  • load_data() (in module deduplipy.datasets)

M

  • MinHashSampler (class in deduplipy.sampling)
  • module
    • deduplipy.blocking
    • deduplipy.classifier_pipeline
    • deduplipy.clustering
    • deduplipy.datasets
    • deduplipy.sampling
    • deduplipy.string_metrics

N

  • NaiveSampler (class in deduplipy.sampling)

P

  • predict() (deduplipy.classifier_pipeline.ClassifierPipeline method)
  • predict_proba() (deduplipy.classifier_pipeline.ClassifierPipeline method)

S

  • sample() (deduplipy.sampling.MinHashSampler method)
    • (deduplipy.sampling.NaiveSampler method)

T

  • transform() (deduplipy.blocking.Blocking method)

© Copyright 2021, Frits Hermans. Revision 9073b449.

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