Remove dots in sub-sub-sections

tex/2_lit/2_class/2_ets.tex

@@ -1,4 +1,4 @@
-\subsubsection{Na\"{i}ve Methods, Moving Averages, and Exponential Smoothing.}
+\subsubsection{Na\"{i}ve Methods, Moving Averages, and Exponential Smoothing}
 \label{ets}
 
 Simple forecasting methods are often employed as a benchmark for more

tex/2_lit/2_class/3_arima.tex

@@ -1,4 +1,4 @@
-\subsubsection{Autoregressive Integrated Moving Averages.}
+\subsubsection{Autoregressive Integrated Moving Averages}
 \label{arima}
 
 \cite{box1962}, \cite{box1968}, and more papers by the same authors in the

tex/2_lit/2_class/4_stl.tex

@@ -1,4 +1,4 @@
-\subsubsection{Seasonal and Trend Decomposition using Loess.}
+\subsubsection{Seasonal and Trend Decomposition using Loess}
 \label{stl}
 
 A time series $y_t$ may exhibit different types of patterns; to fully capture

tex/2_lit/3_ml/2_learning.tex

@@ -1,4 +1,4 @@
-\subsubsection{Supervised Learning.}
+\subsubsection{Supervised Learning}
 \label{learning}
 
 A conceptual difference between classical and ML methods is the format

tex/2_lit/3_ml/3_cv.tex

@@ -1,4 +1,4 @@
-\subsubsection{Cross-Validation.}
+\subsubsection{Cross-Validation}
 \label{cv}
 
 Because ML models are trained by minimizing a loss function $L$, the

tex/2_lit/3_ml/4_rf.tex

@@ -1,4 +1,4 @@
-\subsubsection{Random Forest Regression.}
+\subsubsection{Random Forest Regression}
 \label{rf}
 
 \cite{breiman1984} introduce the classification and regression tree

tex/2_lit/3_ml/5_svm.tex

@@ -1,4 +1,4 @@
-\subsubsection{Support Vector Regression.}
+\subsubsection{Support Vector Regression}
 \label{svm}
 
 \cite{vapnik1963} and \cite{vapnik1964} introduce the so-called support vector

tex/3_mod/7_models/2_hori.tex

@@ -1,4 +1,4 @@
-\subsubsection{Horizontal and Whole-day-ahead Forecasts.}
+\subsubsection{Horizontal and Whole-day-ahead Forecasts}
 \label{hori}
 
 The upper-left in Figure \ref{f:inputs} illustrates the simplest way to

tex/3_mod/7_models/3_vert.tex

@@ -1,4 +1,4 @@
-\subsubsection{Vertical and Whole-day-ahead Forecasts without Retraining.}
+\subsubsection{Vertical and Whole-day-ahead Forecasts without Retraining}
 \label{vert}
 
 The upper-right in Figure \ref{f:inputs} shows an alternative way to

tex/3_mod/7_models/4_rt.tex

@@ -1,4 +1,4 @@
-\subsubsection{Vertical and Real-time Forecasts with Retraining.}
+\subsubsection{Vertical and Real-time Forecasts with Retraining}
 \label{rt}
 
 The lower-left in Figure \ref{f:inputs} shows how models trained on vertical

tex/3_mod/7_models/5_ml.tex

@@ -1,4 +1,4 @@
-\subsubsection{Vertical and Real-time Forecasts without Retraining.}
+\subsubsection{Vertical and Real-time Forecasts without Retraining}
 \label{ml_models}
 
 The lower-right in Figure \ref{f:inputs} shows how ML models take