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what is the value of predicted and actual?

조회 수: 4 (최근 30일)
MANIMEGALAI SELVARAJ
MANIMEGALAI SELVARAJ 2017년 2월 19일
댓글: Monisha R 2021년 10월 7일
function EVAL = Evaluate(ACTUAL,PREDICTED)
% This fucntion evaluates the performance of a classification model by
% calculating the common performance measures: Accuracy, Sensitivity,
% Specificity, Precision, Recall, F-Measure, G-mean.
% Input: ACTUAL = Column matrix with actual class labels of the training
% examples
% PREDICTED = Column matrix with predicted class labels by the
% classification model
% Output: EVAL = Row matrix with all the performance measures
idx = (ACTUAL()==1);
p = length(ACTUAL(idx));
n = length(ACTUAL(~idx));
N = p+n;
tp = sum(ACTUAL(idx)==PREDICTED(idx));
tn = sum(ACTUAL(~idx)==PREDICTED(~idx));
fp = n-tn;
fn = p-tp;
tp_rate = tp/p;
tn_rate = tn/n;
accuracy = (tp+tn)/N;
sensitivity = tp_rate;
specificity = tn_rate;
precision = tp/(tp+fp);
recall = sensitivity;
f_measure = 2*((precision*recall)/(precision + recall));
gmean = sqrt(tp_rate*tn_rate);
EVAL = [accuracy sensitivity specificity precision recall f_measure gmean];

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Star Strider
Star Strider 2017년 2월 19일
From the documenbtation:
% Input: ACTUAL = Column matrix with actual class labels of the training
% examples
% PREDICTED = Column matrix with predicted class labels by the
% classification model
I would assume that ‘matrix’ is ‘vector’ here. The ‘ACTUAL’ values are whatever the original classifications are, and the ‘PREDICTED’ the results of your classifier. The values likely depend on the original ‘correct’ classifications and your classifier output.
  댓글 수: 31
Star Strider
Star Strider 2017년 5월 16일
My pleasure.
Nowshin Jenny
Nowshin Jenny 2018년 12월 19일
Dear sir, after using this command in my code for EEG signal classification, I got following error-
"Function definitions are not permitted in this context."
How can i solve it?

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