evalml.pipelines.components.SMOTESampler.__init__¶
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SMOTESampler.__init__(sampling_ratio=0.25, k_neighbors=5, n_jobs=- 1, random_seed=0, **kwargs)[source]¶ Initializes the oversampler component.
- Parameters
sampling_ratio (float) – This is the goal ratio of the minority to majority class, with range (0, 1]. A value of 0.25 means we want a 1:4 ratio of the minority to majority class after oversampling. We will create the a sampling dictionary using this ratio, with the keys corresponding to the class and the values responding to the number of samples. Defaults to 0.25.
k_neighbors (int) – The number of nearest neighbors to used to construct synthetic samples. Defaults to 5.
n_jobs (int) – The number of CPU cores to use. Defaults to -1.