• BinEdges is a $1xP$ cell of row vectors and ShapeValues a $1xP$ cell of column vectors, as gamboosttrain returns them in the fields of the same names. Each shape function is a step function over its predictor’s bins, so a term is evaluated by a lookup.
• X is an $NxP$ numeric matrix with one column per additive term, and a count that does not match is an error. A missing value contributes nothing from that term rather than making the whole prediction NaN, which is what a tree does with a value it cannot place. A value outside the range the term was fitted over falls in the nearest bin, so a shape function is constant beyond its data rather than extrapolated.
• Intercept is the model’s constant term.
• Link, if given, selects what the additive prediction is mapped through: 0 returns it as it stands and 1 takes it as a log-odds, returning the $Nx2$ matrix of class probabilities whose second column is the logistic function of it. The default is 0.
• PairBinEdges, PairValues and Pairs carry the interaction terms, as gamboostinter returns the first two and as it was given the third. Each pair contributes the value of the cell its two predictors fall in, and a pair with either predictor missing contributes nothing. All three must be given together or none of them.

See also: gamboosttrain, gampredict, ClassificationGAM, RegressionGAM

Source Code: gamboostpredict