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        • Under-Sampling
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  • Input Data
  • Variable Attributes
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  1. Python
  2. Data Preprocess
  3. Highly-Imbalanced Data

Over-Sampling

ADASYN/BorderlineSMOTE/KMeansSMOTE/RandomOverSampler/SMOTE/SMOTENC/SVMSMOTE

PreviousUnder-SamplingNextCombination of over- and under-sampling

Last updated 4 years ago

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Common

Input Data

Inputs

*Target Data

Data input

*Sampler

Name of the user-defined sampler module

*Predict Output

Name of the re-sampled data

*x

Columns (features) to be re-sampled by the sampler, with respect to their labels y.

  • Data type:

    • RamdomOverSampler: all data type.

    • else: numeric.

  • One or more columns should be selected.

*y

Column containing labels of the features x.

  • Only one column should be selected.

Variable Attributes

  • Data Type : Data type of the column (variable); e.g) int64, float64, string...

Python Package

ADASYN:

BorderlineSMOTE:

KMeansSMOTE:

RandomOverSampler:

SMOTE:

SMOTENC:

SVMSMOTE:

https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.ADASYN.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.BorderlineSMOTE.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.KMeansSMOTE.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.RandomOverSampler.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.SMOTE.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.SMOTENC.html
https://imbalanced-learn.readthedocs.io/en/stable/generated/imblearn.over_sampling.SVMSMOTE.htmll
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[Task information of RandomOverSampler]