y and y_hat 1D arrays -> y and y_hat 2D arrays (#189)

Author: madvid

module08/en.subject.tex

@@ -1271,8 +1271,8 @@ \section*{Examples}
 import numpy as np
 from sklearn.metrics import confusion_matrix
 
-y_hat = np.array(['norminet', 'dog', 'norminet', 'norminet', 'dog', 'bird'])
-y = np.array(['dog', 'dog', 'norminet', 'norminet', 'dog', 'norminet'])
+y_hat = np.array([['norminet'], ['dog'], ['norminet'], ['norminet'], ['dog'], ['bird']])
+y = np.array([['dog'], ['dog'], ['norminet'], ['norminet'], ['dog'], ['norminet']])
 
 # Example 1: 
 ## your implementation
@@ -1331,8 +1331,8 @@ \subsection{Instructions:}
 \section{Examples:}
 \begin{minted}[bgcolor=darcula-back,formatcom=\color{lightgrey},fontsize=\scriptsize]{python}
 import numpy as np
-y_hat = np.array(['norminet', 'dog', 'norminet', 'norminet', 'dog', 'bird'])
-y_true = np.array(['dog', 'dog', 'norminet', 'norminet', 'dog', 'norminet'])
+y_hat = np.array([['norminet'], ['dog'], ['norminet'], ['norminet'], ['dog'], ['bird']])
+y_true = np.array([['dog'], ['dog'], ['norminet'], ['norminet'], ['dog'], ['norminet']])
 
 # Example 1: 
 confusion_matrix_(y_true, y_hat, df_option=True)

version

@@ -1 +1 @@
-v4.0.4
+v4.0.5