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113 lines
2.9 KiB
C
113 lines
2.9 KiB
C
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#pragma once
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//
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// FILE: GST.h
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// VERSION: 0.1.0
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// PURPOSE: Arduino library for Gold Standard Test metrics
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// URL: https://github.com/RobTillaart/GST
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// https://en.wikipedia.org/wiki/Sensitivity_and_specificity
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// https://en.wikipedia.org/wiki/Confusion_matrix
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//
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// formula's based upon wikipedia.
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#define GST_LIB_VERSION (F("0.1.0"))
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class GST
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{
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public:
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GST() {};
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// These 4 need to be filled in.
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void setTruePositive(float v) { TP = v; P = TP + FN; };
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void setTrueNegative(float v) { TN = v; N = TN + FP; };
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void setFalsePositive(float v) { FP = v; N = TN + FP; };
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void setFalseNegative(float v) { FN = v; P = TP + FN; };
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float getTruePositive() { return TP; };
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float getTrueNegative() { return TN; };
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float getFalsePositive() { return FP; };
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float getFalseNegative() { return FN; };
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float getTotal() { return P + N; };
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float getActualPositive() { return P; };
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float getActualNegative() { return N; };
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float getTestedPositive() { return TP + FP; };
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float getTestedNegative() { return TN + FN; };
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float sensitivity() { return TPR(); };
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float specificity() { return TNR(); };
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// true positive rate
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float TPR() { return TP / P; };
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// true negative rate
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float TNR() { return TN / N; };
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// false negative rate
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float FNR() { return FN / (FN + TP); };
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// false positive rate
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float FPR() { return FP / (FP + TN); };
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// positive predictive value
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float PPV() { return TP / (TP + FP); };
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// negative predictive value
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float NPV() { return TN / (TN + FN); };
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// false discovery rate
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float FDR() { return FP / (FP + TP); };
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// false omission rate
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float FOR() { return FN / (FN + TN); };
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// positive likelihood ratio
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float LRplus() { return TPR() / FPR(); };
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// negative likelihood ratio
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float LRminus() { return FNR() / TNR(); };
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float prevalenceThreshold() { return sqrt(FPR()) / (sqrt(TPR()) + sqrt(FPR())); };
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float threatScore() { return TP / (TP + FN + FP); };
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float criticalSuccessIndex() { return threatScore(); };
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float prevalence() { return P / (P + N); };
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float accuracy() { return (TP + TN) / (P + N); };
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float balancedAccuracy() { return (TPR() + TNR()) / 2; };
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float F1Score() { return (2 * TP)/(2 * TP + FP + FN); };
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// Matthews correlation coefficient
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float MCC() { return (TP*TN-FP*FN)/sqrt((TP+FP)*(TP+FN)*(TN+FP)*(TN+FN)); };
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float phi() { return MCC(); };
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// Fowlkes–Mallows index
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float FM() { return sqrt(PPV()*TPR()); };
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// Bookmaker informedness
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float BM() { return TPR() + TNR() - 1; };
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// markedness
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float MK() { return PPV() + NPV() - 1; };
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float deltaP() { return MK(); };
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// diagnostic odds ratio
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float DOR() { return LRplus() / LRminus(); };
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private:
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float P = 0;
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float N = 0;
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float TP = 0;
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float TN = 0;
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float FP = 0;
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float FN = 0;
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};
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// -- END OF FILE --
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