| #------------------------------------------------------------- |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| #------------------------------------------------------------- |
| |
| |
| args <- commandArgs(TRUE) |
| options(digits=22) |
| |
| library("Matrix") |
| |
| X <- as.matrix(readMM(paste(args[1], "X.mtx", sep=""))) |
| W <- as.matrix(readMM(paste(args[1], "W.mtx", sep=""))) |
| |
| Nt = nrow(X); |
| num_classes = ncol(W) |
| n = ncol(X); |
| |
| b = W[n+1,] |
| ones = matrix(1, Nt, 1) |
| scores = X %*% W[1:n,] + ones %*% b; |
| |
| predicted_y = max.col(scores,ties.method="last") |
| |
| writeMM(as(predicted_y, "CsparseMatrix"), paste(args[2], "predicted_y", sep="")); |
| |
| |
