Parameters of trained algorithms. - Swathi Anil (17382903) (2025)
Learned parameter weights. Each subplot shows the weights learned by a single model (LF, NLF, NLF2 and NLF3). Each x-axis shows the value of k used to train the model. Each y-axis shows possible observations / features. For example ; sorted by their total corresponding parameter value (summed across values of k). Intuitively, ambiguous signals tend to be assigned low/zero weights. For example, . While, unambigous signals, tend to be assigned larger weights. For example, . And NLFw seems to learn different patterns when k<w vs when . Though we did not quantify these observations. (TIFF)