5887 quot 8659 8884 quot rMNa quot quot rMNa için arama sonuçları

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RMNA(X, Y) X is the input data sample (one- or two-dimensional array of cells). Y is an auxiliary (optional) data sample (one- or two-dimensional array of cells). Remarks. Each input (or auxiliary) data set column corresponds to a separate variable. Each row in the input (or in the auxiliary) data set corresponds to an observation.

rmna forms an object of class, repeated, from a response object and possibly time-varying or intra-individual covariate ( tvcov ), and time-constant or inter-individual covariate ( tccov) objects, removing any observations where response and covariate values have NAs. Subjects must be in the same order in all (three) objects to be combined.

This repository contains a Pytorch implementation of RMNA. We use AMIE to obtains horn rules. RMNA is a hierarchical neighbor aggregation model, which transforms valuable multi-hop neighbors into one-hop neighbors that are semantically similar to the corresponding multi-hop neighbors, so that the completeness of multi-hop neighbors can be ensured.

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utilized by aggregating transformed one-hop neighbors. The main contributions of RMNA are summarized as follows: Propose RMNA, which transforms valuable multi-hop neighbors into one-hop neighbors that are semantically similar to the corresponding multi-hop neighbors, so that the completeness of multi-hop neighbors can be ensured.

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