Lloyd's Algorithm is an iterative method used for vector quantization that aims to minimize the distortion between the input data and its quantized representation by adjusting the positions of the codewords. The algorithm alternates between assigning data points to the nearest codeword and recalculating the codewords based on the assigned data points. This process continues until convergence is achieved, making it an effective technique in competitive learning and clustering tasks.
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