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Early detection of Autism Spectrum Disorder (ASD) is challenging due to manual screening methods. This project aims to develop a machine learning model to predict ASD based on behavioral and personal features.

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Autism Screening using Machine Learning

Objective

To predict Autism Spectrum Disorder (ASD) using machine learning techniques.

Models Used

  • Logistic Regression
  • Decision Tree
  • Random Forest

Evaluation Metrics

  • Accuracy
  • Precision
  • Recall
  • F1 Score
  • Confusion Matrix

Result

Random Forest performed best based on F1 Score.

Tools Used

  • Python
  • Google Colab
  • Scikit-learn

About

Early detection of Autism Spectrum Disorder (ASD) is challenging due to manual screening methods. This project aims to develop a machine learning model to predict ASD based on behavioral and personal features.

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