| #------------------------------------------------------------- |
| # |
| # 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. |
| # |
| #------------------------------------------------------------- |
| |
| # This function calls the multiLogReg-function in which solves Multinomial |
| # Logistic Regression using Trust Region method |
| # |
| # INPUT: |
| # ------------------------------------------------------------------------------------- |
| # X matrix of feature vectors |
| # Y matrix with category labels |
| # threshold threshold to clear otherwise return X and Y unmodified |
| # verbose flag specifying if logging information should be printed |
| # ------------------------------------------------------------------------------------- |
| # |
| # OUTPUT: |
| # ------------------------------------------------------------------------------------- |
| # Xout abstained output X |
| # Yout abstained output Y |
| # ------------------------------------------------------------------------------------- |
| |
| m_abstain = function(Matrix[Double] X, Matrix[Double] Y, Double threshold, Boolean verbose = FALSE) |
| return (Matrix[Double] Xout, Matrix[Double] Yout) |
| { |
| Xout = X |
| Yout = Y |
| if(min(Y) != max(Y) & max(Y) <= 2) |
| { |
| betas = multiLogReg(X=X, Y=Y, icpt=1, reg=1e-4, maxi=100, maxii=0, verbose=verbose) |
| [prob, yhat, accuracy] = multiLogRegPredict(X, betas, Y, FALSE) |
| |
| inc = ((yhat != Y) & (rowMaxs(prob) > threshold)) |
| if(sum(inc) > 0) |
| { |
| Xout = removeEmpty(target = X, margin = "rows", select = (inc == 0) ) |
| Yout = removeEmpty(target = Y, margin = "rows", select = (inc == 0) ) |
| } |
| } |
| } |