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Remove whitespace between letters of two-letter variables

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Charlotte Van Petegem 2024-06-06 15:49:21 +02:00
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@ -2439,17 +2439,17 @@ The latter is also called sensitivity if used in combination with specificity (E
#+NAME: eq:precision #+NAME: eq:precision
\begin{equation} \begin{equation}
\frac{TP}{TP+FP} \frac{\mathit{TP}}{\mathit{TP}+\mathit{FP}}
\end{equation} \end{equation}
#+NAME: eq:recall #+NAME: eq:recall
\begin{equation} \begin{equation}
\frac{TP}{TP+FN} \frac{\mathit{TP}}{\mathit{TP}+\mathit{FN}}
\end{equation} \end{equation}
#+NAME: eq:specificity #+NAME: eq:specificity
\begin{equation} \begin{equation}
\frac{TN}{TN+FP} \frac{\mathit{TN}}{\mathit{TN}+\mathit{FP}}
\end{equation} \end{equation}
Many studies for pass/fail prediction use accuracy (Equation\nbsp{}[[eq:accuracy]]) as a single performance metric. Many studies for pass/fail prediction use accuracy (Equation\nbsp{}[[eq:accuracy]]) as a single performance metric.
@ -2459,7 +2459,7 @@ This is clearly a bad classifier, but it will nonetheless have an accuracy of 75
#+NAME: eq:accuracy #+NAME: eq:accuracy
\begin{equation} \begin{equation}
\frac{TP+TN}{TP+TN+FP+FN} \frac{\mathit{TP}+\mathit{TN}}{\mathit{TP}+\mathit{TN}+\mathit{FP}+\mathit{FN}}
\end{equation} \end{equation}
In our study, we will therefore use two more complex metrics that take these effects into account: balanced accuracy and F_1-score. In our study, we will therefore use two more complex metrics that take these effects into account: balanced accuracy and F_1-score.