predict.nmfkc.signed: Predict method for nmfkc.signed

In nmfkc: Non-Negative Matrix Factorization with Kernel Covariates

Predict method for nmfkc.signed

Description

Computes \widehat Y = X \, C \, A_{\mathrm{new}} (= X (C_{+} - C_{-})(A_{+}^{\mathrm{new}} - A_{-}^{\mathrm{new}})). For type = "response" the raw prediction is returned (possibly signed). For type = "prob" and "class", negative entries of \widehat Y are clipped to zero before column normalization, since probabilities must be non-negative.

Usage

## S3 method for class 'nmfkc.signed'
predict(object, newA = NULL, type = c("response", "prob", "class"), ...)

Arguments

object	A fitted "nmfkc.signed" object.
newA	Real-valued D \times N_{\mathrm{new}} covariate matrix.
type	Output: "response" (raw signed), "prob", or "class".
...	Unused.

Value

A numeric matrix ("response" or "prob") or a character vector ("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.

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