ANVO SMOTE

The ANVO algorithm, a variant of SMOTE, targets class imbalances by enriching the minority class with synthetic data. It assesses the distribution and relationships within the minority class to create new, meaningful samples. By adapting the neighbor analysis based on class density, ANVO ensures the generated instances enhance the diversity and coverage of the minority class in underrepresented areas of the feature space. This approach aims to balance the dataset, improving the performance of machine learning models by providing a more representative sample distribution.

from sdgne.datagenerator.smote import ANVO

minority_column_label = 'class'
minority_class_label = 0

synthesizer = ANVO(dataset,minority_column_label,minority_class_label)

synthesize_data = synthesizer.data_generator()

Importing SMOTE

from sdgne.datagenerator.smote import ANVO

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Creating a synthesizer

synthesizer = ANVO(dataset, minority_column_label, minority_class_label)

Parameters

dataset	required	pd.Dataframe	Represents a pandas data frame containing both, the original minority and the original majority data.
minority_column_label	required	string	Represents the column label. Eg. 'class', 'output'
minority_class_label	required	string	Represents the minority class label. Eg. '1', '0'

Returns

An instance of class SDD_SMOTE.

Synthetic Data Generation

data_generator()

The data generator function generates synthetic data using the synthesizer. It has an option parameter num_to_synthesize.

• If num_to_synthesize is not defined, data_generator by default generates the `n` number of synthetic data such that the majority data and minority datasets get balanced.

• If num_to_synthesize is defined and the dataset is already balanced, data_generator generates 2 * Number of original minority data.

• If num_to_synthesize is defined and the dataset is not balanced, it generates synthetic data equal to the value passed.

synthesized_data = synthesizer.data_generator(no_of_syntetic_data)

Parameters

num_to_synthesize	optional (default: None)	integer	Represents the number of synthetic data to be generated.

Returns

A pandas data frame that combines original data and synthetic data.

Usage

synthesizer.data_generator()

synthesizer.data_generator(num_to_synthesize=100)