wrapper methodの例文

• Wrapper methods use a predictive model to score feature subsets.
• Methods for selecting features fall into two categories : filter methods and wrapper methods.
• "Self-training " is a wrapper method for semi-supervised learning.
• You may use most Buffer object functions normally, however if there is a wrapper method that merely redirects the self-action to the outside Buffer-HTML.
• As wrapper methods train a new model for each subset, they are very computationally intensive, but usually provide the best performing feature set for that particular type of model.
• Functions from these libraries added to the Module : Buffer metatable on-demand and placed within a wrapper method that strings the Buffer object for the first argument and then forwards the remaining arguments.