"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.
Offline Python classifier that predicts gender associations from names. 49KB model, no API needed.
NamSor API v2 GO golang SDK - classify personal names accurately by gender, country of origin, or ethnicity.
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.
A small Laravel API for classifying a given first name using the Genderize API.
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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