minor typos

src/performance.Rmd

@@ -183,7 +183,7 @@ r = calculateROCMeasures(pred)
 r
 ```
 
-The topleft 2 times 2 matrix is the [confusion matrix](predict.md#Confusion_matrix), so that we can see
+The top left 2 times 2 matrix is the [confusion matrix](predict.md#Confusion matrix), so that we can see
 the relative frequency of correctly and incorrectly classified observations. Then a large number of
 additional measures is added to the matrix that can be used to evaluate the model performance. Explainations of 
 the abbreviations is also returned as well as further common names for some measures. The printing of the

src/predict.Rmd

@@ -144,7 +144,7 @@ calculateConfusionMatrix(pred)
 
 We can see that correctly classified observation are on the diagonal of the matrix. Missclassifified 
 observations are on the off-diagonal. It is possible to marginalize over the classes and number of errors
-in one class is shown in the `-err.-` row and column. THe resulting object hast the class [&ConfMatrix]
+in one class is shown in the `-err.-` row and column. The resulting object hast the class [&ConfMatrix]
 where its structure is explained in detail.
 
 To get relative frequencies as well as absolute numbers we can set `relative=TRUE`.