to do for logreg

2019-09-17 22:31:23 +02:00
parent e267645632
commit d0adb4b485
1 changed files with 6 additions and 1 deletions
@@ -61,7 +61,12 @@ made of $n$ samples, each of which carries $p$ features or predictors. The
 primary goal is to identify the classes to which new unseen samples
 belong.
 
-Let us specialize to the case of two classes only, with outputs $y_i=0$ and $y_i=1$. Our outcomes could represent the status of a credit card user who could default or not on her/his credit card debt. That is
+Let us specialize to the case of two classes only, with outputs
+$y_i=0$ and $y_i=1$. Our outcomes could represent the status of a
+credit card user that could default or not on her/his credit card
+debt. That is
+
+
 !bt
 \[
 y_i = \begin{bmatrix} 0 & \mathrm{no}\\  1 & \mathrm{yes} \end{bmatrix}.