smote etymology

Etymology

The term "SMOTE" is an acronym that stands for "Synthetic Minority Over-sampling Technique".

Meaning

SMOTE is an oversampling technique used in machine learning to address the problem of class imbalance. Class imbalance occurs when a dataset contains a significantly different number of instances for different classes, making it difficult for machine learning models to learn effectively.

Origin

SMOTE was developed by Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, and W. Philip Kegelmeyer in 2002. They published their findings in a paper titled "SMOTE: Synthetic Minority Over-sampling Technique" in the Journal of Artificial Intelligence Research.

How SMOTE Works

SMOTE works by generating synthetic instances for the minority class. It does this by randomly selecting a minority class instance and then finding its nearest neighbors. One of the nearest neighbors is then randomly selected, and a new synthetic instance is created by interpolating between the two instances.

By generating synthetic instances, SMOTE increases the number of minority class instances in the dataset, which helps to balance the class distribution. This, in turn, improves the performance of machine learning models by reducing bias towards the majority class.

smote relate terms

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  Etymology Origin Old English smītan Proto Germanic smītanan Proto Indo European

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  Etymology The word strike comes from the Middle English word striken which is derive

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  Etymology The word damage comes from the Old French word damager which means to inj

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  Etymology The word impress comes from the Latin verb imprimō meaning to press upon

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  Etymology Derived from the Latin word afficere meaning to do something to or to ha

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  Etymology The word plague comes from the Latin word plaga which means blow or wo

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  Etymology Middle English blīte from Old English blīht joyful cheerful gracious

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  Etymology The word move is derived from the Middle English muven which in turn came

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  Etymology Latin visitare from visere meaning to go to see Ultimately derived fr