LASSO tuning parameter selection
The LASSO is a penalized regression method which simultaneously performs shrinkage and variable selection. The output produced by the LASSO consists of a piecewise linear solution path, starting with the null model and ending with the full least squares fit, as the value of a tuning parameter is decreased. The performance of the selected model therefore depends greatly on the choice of this parameter. This paper attempts to provide an overview of methods which are available to select the value of the tuning parameter for either prediction or variable selection purposes. A simulation study provides a comparison of these methods and assesses their performance.
-We describe a simple method to generate wavelength-tunable pulses by using a semiconductor optical amplifier (SOA) as an intensity modulator and a gain medium. Wavelength tunable pulses at a repetition rate of 4.8 GHz have been generated.