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

Data Mining project to implement Quinlan's C4.5 decision tree algorithm from scratch for medical data mining using the Thyroid allbp dataset

Thyroid Syndrome Detection using Machine Learning Algorithms 🔬

A sklearn-driven script to learn the best parameters for MLP to classify a thyroid dataset

Implementation of decision tree from scratch using numpy and pandas only. Supports both type of cost function, information gain as well as gini index

Accuracy- 98.7% on predicting the presence or absence of Thyroid

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