predict.nmfae.signed: Predict method for nmfae.signed

In nmfkc: Non-Negative Matrix Factorization with Kernel Covariates

Predict method for nmfae.signed

Description

Computes \hat Y_1 = X_1 (C_{+} - C_{-}) X_2 Y_2^{\mathrm{new}}. Since \Theta = C_{+} - C_{-} is signed, predictions may contain negative entries even when Y_1 \ge 0 in training.

Usage

## S3 method for class 'nmfae.signed'
predict(object, newY2 = NULL, Y1 = NULL, type = c("response", "class"), ...)

Arguments

object	A fitted "nmfae.signed" object.
newY2	New input matrix (P2 x N_new). If NULL, returns the training fitted values.
Y1	Optional reference Y1 for scatter / confusion plot.
type	Output: "response" (raw signed) or "class".
...	Unused.

Value

A numeric matrix ("response") or factor ("class").

Lifecycle

This function is experimental. The interface may change in future versions.

References

Ding, C. H. Q., Li, T., & Jordan, M. I. (2010). Convex and semi-nonnegative matrix factorizations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(1), 45–55.

See Also

nmfae.signed

nmfkc documentation built on July 14, 2026, 1:07 a.m.