| #------------------------------------------------------------- |
| # |
| # 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. |
| # |
| #------------------------------------------------------------- |
| |
| # compute the weighted and simple accuracy for given predictions |
| |
| # Built-in function Implements Multiple Imputation using Chained Equations (MICE) |
| # |
| # INPUT PARAMETERS: |
| # --------------------------------------------------------------------------------------------- |
| # NAME TYPE DEFAULT MEANING |
| # --------------------------------------------------------------------------------------------- |
| # y Double --- Ground truth (Actual Labels) |
| # yhat Double --- predictions (Predicted labels) |
| # isWeighted Boolean FALSE flag for weighted or non-weighted accuracy calculation |
| # --------------------------------------------------------------------------------------------- |
| |
| |
| #Output(s) |
| # --------------------------------------------------------------------------------------------- |
| # NAME TYPE DEFAULT MEANING |
| # --------------------------------------------------------------------------------------------- |
| # accuracy Double --- accuracy of the predicted labels |
| |
| |
| m_getAccuracy = function(Matrix[Double] y, Matrix[Double] yhat, Boolean isWeighted = FALSE) |
| return (Double accuracy) |
| { |
| if(isWeighted) |
| { |
| sum = sum(y == yhat) |
| accuracy = (sum/nrow(y)) * 100 |
| } |
| else |
| { |
| n = nrow(y) |
| classes = table(y, 1) |
| class_weight = n/(nrow(classes) * classes) |
| resp = matrix(0, nrow(y), nrow(classes)) |
| resp = resp + t(seq(1, nrow(classes))) |
| |
| respY = resp == y |
| respYhat = resp == yhat |
| |
| pred = respY * respYhat |
| classes = replace(target = classes, pattern = 0, replacement = 1) |
| accuracy = mean(colSums(pred)/t(classes)) * 100 |
| } |
| |
| } |