Update README.md

Author: vba34520

README.md

@@ -8,17 +8,15 @@
 
 ## Standard
 
-<img src="https://latex.codecogs.com/gif.latex?\mathrm{Accuracy}=\frac{\mathrm{TP}&plus;\mathrm{TN}}{\mathrm{P}&plus;\mathrm{N}}" title="\mathrm{Accuracy}=\frac{\mathrm{TP}+\mathrm{TN}}{\mathrm{P}+\mathrm{N}}" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{Accuracy=\frac{TP&plus;TN}{P&plus;N}}" title="\mathrm{Accuracy=\frac{TP+TN}{P+N}}" />
 
-<img src="https://latex.codecogs.com/png.latex?Accuracy=\frac{TP&plus;TN}{P&plus;N}" title="Accuracy=\frac{TP+TN}{P+N}" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{ErrorRate=1-Accuracy}" title="\mathrm{ErrorRate=1-Accuracy}" />
 
-<img src="https://latex.codecogs.com/png.latex?ErrorRate=1-Accuracy" title="ErrorRate=1-Accuracy" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{Precision=\frac{TP}{TP&plus;FP}}" title="\mathrm{Precision=\frac{TP}{TP+FP}}" />
 
-<img src="https://latex.codecogs.com/png.latex?Precision=\frac{TP}{TP&plus;FP}" title="Precision=\frac{TP}{TP+FP}" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{Recall=\frac{TP}{TP&plus;FN}}" title="\mathrm{Recall=\frac{TP}{TP+FN}}" />
 
-<img src="https://latex.codecogs.com/png.latex?Recall=\frac{TP}{TP&plus;FN}" title="Recall=\frac{TP}{TP+FN}" />
-
-<img src="https://latex.codecogs.com/png.latex?F1=\frac{2×TP}{n\_samples&plus;TP-TN}" title="F1=\frac{2×TP}{n\_samples+TP-TN}" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{F1=\frac{2×TP}{n\_samples&plus;TP-TN}}" title="\mathrm{F1=\frac{2×TP}{n\_samples+TP-TN}}" />
 
 Confusion matrix
 
@@ -31,13 +29,13 @@ Confusion matrix
 
 The vertical axis of the ROC(Receiver Operating Characteristic) curve is TPR(True Positive Rate) and the horizontal axis is FPR(False Positive Rate).
 
-<img src="https://latex.codecogs.com/png.latex?TPR=\frac{TP}{TP&plus;FN}" title="TPR=\frac{TP}{TP+FN}" />
+<img src="https://latex.codecogs.com/gif.latex?\mathrm{TPR=\frac{TP}{TP&plus;FN}}" title="\mathrm{TPR=\frac{TP}{TP+FN}}" />
 
-<img src="https://latex.codecogs.com/png.latex?FPR=\frac{FP}{TN&plus;FP}" title="FPR=\frac{FP}{TN+FP}" />
+<img src="https://latex.codecogs.com/png.latex?\mathrm{FPR=\frac{FP}{TN&plus;FP}}" title="FPR=\frac{FP}{TN+FP}" />
 
 AUC is the area under ROC curve.
 
-<img src="https://latex.codecogs.com/png.latex?AUC=\frac{1}{2}\sum_{i=1}^{m-1}(x_{i&plus;1}-x_{i})*(y_{i}&plus;y_{i&plus;1})" title="AUC=\frac{1}{2}\sum_{i=1}^{m-1}(x_{i+1}-x_{i})*(y_{i}+y_{i+1})" />
+<img src="https://latex.codecogs.com/png.latex?\mathrm{AUC}=\frac{1}{2}\sum_{i=1}^{m-1}(x_{i&plus;1}-x_{i})*(y_{i}&plus;y_{i&plus;1})" title="AUC=\frac{1}{2}\sum_{i=1}^{m-1}(x_{i+1}-x_{i})*(y_{i}+y_{i+1})" />
 
 ![ROC](https://github.com/vba34520/Classification-Performance-Standard/blob/master/picture/ROC.png)