hassanzadehmahdi / classifying-thyroid-disease-dataset-using-multi-layer-perceptron

An implementation of multi-layer perceptron for classifying thyroid disease dataset

Classifying-Thyroid-Disease-Dataset-using-Multi-Layer-Perceptron

The "Multi-layer Perceptron Implementation for Thyroid Disease Classification" project focuses on developing an accurate and robust classification system using a multi-layer perceptron (MLP) algorithm. By leveraging a diverse thyroid disease dataset, the project aims to effectively analyze and categorize cases of thyroid diseases. The dataset is preprocessed to ensure high-quality input, and an MLP architecture is implemented using deep learning frameworks. Through training and optimization techniques, the model learns from the labeled data, and its performance is evaluated using various metrics. The project aims to provide valuable insights into the effectiveness of MLPs in thyroid disease classification, contributing to improved diagnostic accuracy and healthcare outcomes.

An example of running the program: