"The Importance of being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-based Ethnicity Classification" Authors: Vaishali Jain, Ted Enamorado, and Cynthia Rudin
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Updated
Jan 6, 2023 - R
"The Importance of being Ernest, Ekundayo, or Eswari: An Interpretable Machine Learning Approach to Name-based Ethnicity Classification" Authors: Vaishali Jain, Ted Enamorado, and Cynthia Rudin
A lightweight machine learning model for gender prediction based on Rwandan names using character-level n-gram features and logistic regression.
NamSor API v2 GO golang SDK - classify personal names accurately by gender, country of origin, or ethnicity.
Offline Python classifier that predicts gender associations from names. 49KB model, no API needed.
A small Laravel API for classifying a given first name using the Genderize API.
This project proposes a system that infers the most likely country or region of origin for a given first and last name. The output is a ranked list of countries with confidence scores, designed to support sanctions and watchlist matching in an AML system.
This project uses Recurrent Neural Networks (RNNs) to predict the language or country origin of a name based on its character sequence.
Indonesian personal-name gender classification using character-level, word-level, Transformer, BiLSTM, BiGRU, BERT and classical ML models.
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