What is Curse of Dimensionality?
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Hello everyone!!! Today's Q&A in Data Science!! 🖥️📊🔢 What is the Curse of Dimensionality? 📚📖📝 1. Overview The curse of dimensionality refers to the phenomenon where the density of data points becomes extremely sparse in high-dimensional space. It poses challenges in processing and analyzing high-dimensional data, leading to a reduction in the accuracy of learning and prediction. 2. Issues - Increased data sparsity: In high-dimensional space, data becomes sparse, and the distances between data points tend to become more significant. - Increased computational complexity: The computational cost required for processing high-dimensional data increases exponentially, resulting in significant resource consumption. - Increased risk of overfitting: In high-dimensional space, the model becomes excessively fitted to the training data, leading to overfitting, where it fails to generalize well to new data. 3. Examples and Solutions - Example: In high dimensions, the K-Nearest Neighbor...