<title>Abstract</title> Data preprocessing stages, including data reconstruction and dimensionality reduction, play a pivotal role in influencing subsequent machine learning and data mining endeavors. While supervised dimensionality reduction typically surpasses unsupervised methods through direct label exploitation, the scarcity or high acquisition cost of labeled data in practical scenarios has fueled interest in semi-supervised alternatives. These methodologies ingeniously integrate sparse labeled and abundant …