Python, Machine Learning, Optimization, Implementation, Theory.
discarding wavelet coefficients. It controls the aggressiveness of dimensionality reduction. Experiment with different values (e.g., 0.05, 0.2) to find the optimal balance for your data. Higher thresholds discard more coefficients, leading to greater reduction but potentially losing information. 4.