NCAE

NCAE, or Neural Clustering AutoEncoder, is a machine learning technique that combines two methods: autoencoders and clustering. Autoencoders learn to compress and then reconstruct data, capturing essential features efficiently. When combined with clustering, NCAE groups similar data points together based on these features, revealing natural patterns or segments within complex datasets. This approach helps in understanding data structures without prior labels, making it useful for tasks like customer segmentation, image analysis, and pattern discovery, by providing clear, meaningful groupings while reducing data complexity.