Model performance with accuracy of 99.904%, precision of 99.871%, recall of 99.877%, and f1-score of 99.874% with 96799 training data and 24200 testing data.
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Updated
Feb 5, 2024 - Jupyter Notebook
Model performance with accuracy of 99.904%, precision of 99.871%, recall of 99.877%, and f1-score of 99.874% with 96799 training data and 24200 testing data.
This project will make predictions and a little PHP-based visualization, machine learning here will describe the predictions of whether you are stunting (nutritional problems) or not.
👶ASING! Machine Learning Model (Bangkit Capstone Project 2024 Batch 1)
predictive analysis yang dapat memprediksi tingkat risiko stunting pada anak berdasarkan faktor-faktor gizi dalam makanan ibu hamil, dengan tingkat akurasi yang tinggi.
Analysis of 3 measurements of malnutrition in young children globally and comparing it to the COVID-19 death rates.
An AI-powered medical app addressing child stunting👶 innovatively optimizes growth and development, streamlining health monitoring, offering timely nutrition guidance, and transforming child care practices, potentially preventing long-term health issues for future generations 🥑.
MARS Modeling: Nutrition for Stunting in Depok, Indonesia
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