| #------------------------------------------------------------- |
| # |
| # 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") |
| library("nnet") |
| |
| X = as.matrix(readMM(paste(args[1], "A.mtx", sep=""))) |
| Y = as.matrix(readMM(paste(args[1], "B.mtx", sep=""))) |
| X_test = as.matrix(readMM(paste(args[1], "C.mtx", sep=""))) |
| Y_test = as.matrix(readMM(paste(args[1], "D.mtx", sep=""))) |
| |
| X = cbind(Y, X) |
| X_test = cbind(Y_test, X_test) |
| X = as.data.frame(X) |
| # set a baseline variable |
| X$V1 <- relevel(as.factor(X$V1), ref = "3") |
| X_test = as.data.frame(X_test) |
| model = multinom(V1~., data = X) # train model |
| pred <- predict(model, newdata = X_test, "class") # predict unknown data |
| acc = (sum(pred == Y_test)/nrow(Y_test))*100 |
| |
| writeMM(as(as.matrix(acc), "CsparseMatrix"), paste(args[2], "O", sep="")) |
