Hyperspectral imaging (HSI) captures rich spectral data across hundreds of contiguous bands for diverse applications. Dimension reduction (DR) techniques are commonly used to map the first three ...
The final, formatted version of the article will be published soon. This study presents a comprehensive framework for solar radiation forecasting (SRF) by integrating Principal Component Analysis (PCA ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...
ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...
PCA + MiniBatch KMeans offers a strong trade-off between performance and computational cost. SAE + DBSCAN produces high-quality clusters but requires significantly more training time. Visual ...
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Abstract: PCA algorithm is a typical data dimensionality reduction method, which projects high-dimensional data to a lower-dimensional space to obtain a low-dimensional data set that can maximally ...
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