Preprocessing refers to the steps taken to prepare raw data for analysis, ensuring that it is clean, organized, and suitable for the intended purpose. This process is crucial as it helps eliminate noise, reduce dimensionality, and enhance the quality of the data, which is especially important when using techniques like t-SNE and UMAP that are sensitive to data quality and structure.
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