Merge overleaf-2024-11-08-1929 into master

slides/supervised-classification/slides-classification-naivebayes.tex

@@ -42,8 +42,10 @@
 
 We use a univariate Gaussian for $p(x_j | y=k)$, and estimate $(\mu_{kj}, \sigma^2_{kj})$ in the standard manner. Because of $\pdfxyk = \prodjp p(x_j|y = k)$, the joint conditional density is Gaussian with diagonal but non-isotropic covariance structure, and potentially different across classes.
 
+\lz
+
 \begin{center}
-\includegraphics[width=0.2\textwidth]{figure/nb-db.png} 
+\includegraphics[width=0.6\textwidth, clip = true, trim = {0 100 0 120}]{figure/nb-db.png} 
 \end{center}
 
 $\Rightarrow$  \textbf{NB is a} (specific) \textbf{QDA model}, with a quadratic decision boundary.