New hybrid feature extraction technique boosts machine learning accuracy by 15%!
Feature extraction is crucial for improving machine learning systems. A new method called PCSVD combines PCA and SVD to reduce data dimensions and enhance classifier performance. Compared to other techniques like ICA, PCA, LDA, and SVD, PCSVD shows better accuracy, sensitivity, specificity, and precision. It also reduces dimensionality and error rates significantly, making it a promising approach for real-world applications.