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Minority Groups

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The Impact of Oversampling with SMOTE on the Performance of 3 Classifiers in Prediction of Type 2 Diabetes.

Medical decision making : an international journal of the Society for Medical Decision Making Jan 1, 2016
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision tree (DT) classifiers for predicting diabetes in a prospective cohort ...
Adult Algorithms Bayes Theorem Decision Trees Diabetes Mellitus, Type 2 Female Humans Iran Male Middle Aged Minority Groups Models, Theoretical Neural Networks, Computer Prospective Studies Risk Factors Selection Bias Sensitivity and Specificity Socioeconomic Factors
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Word embeddings quantify 100 years of gender and ethnic stereotypes.

Proceedings of the National Academy of Sciences of the United States of America Apr 17, 2018
Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we de...
Culture Ethnicity Female History, 20th Century History, 21st Century Humans Internet Language Machine Learning Male Minority Groups Newspapers as Topic Occupations Racism Religion Sexism Social Change Stereotyping United States
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