- Data Mining Course (2023)
This repository contains implementations of four different models to predict chronic kidney disease in patients based on blood tests.
The models included in this project are:
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Naive Bayes is a probabilistic classifier based on Bayes' theorem with the assumption of independence between features. It is well-suited for handling high-dimensional data and is computationally efficient.
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K Nearest Neighbors (KNN) is a simple and intuitive classification algorithm that assigns a class label to an instance based on the majority class of its K nearest neighbors in the feature space.
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K Means Clustering is an unsupervised learning algorithm used for clustering data into K distinct clusters. It aims to partition data points into clusters such that points within the same cluster are more similar to each other than to those in other clusters.
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Connected Neural Network, or a multi-layer perceptron (MLP), is a deep learning model capable of learning complex patterns and representations from data.