## 3 Materials and Methods
### Data Collection  
Our study covers the period from May to August, 2018, and monitors animals at a Holstein-Friesian dairy cow farm in Karnobat region, Southeastern Bulgaria. The animals within our samples are raised via free box breeding in a building of semi-open type, with a full-year feeding on a voluntary basis with a mixed diet. Measurements are made twice a day at 10 am and 5 pm. Thermographic images are captured with the FLIR E6 thermal camera. The temperature-humidity index (THI) is reported with the aid of the Kestrel automatic measuring device. All measurements are carried out at the same time in the premises for keeping the cow, as well as the physiological indicators of each cow-- rectal temperature, heart rate, and breathing intensity. The calculations of these physiological indicators is done by separating and fixing the cows. Rectal temperature is measured in degrees Celsius by placing a digital thermometer in the rectum. The intensity of respiration was measured by visual observation, and the movement of the chest was measured for a period of one minute, according to the methodology of [PERSON] et al. (2009) [57].  
Figure 1: Infrared images of dairy cows from different angles.  
The pulse rate recording was performed manually on the occipital artery. All of this requires time and water until the stress is known, which is reflected in the values of some indicators, especially in respiration [57]. In Table 1, we present some basic statistical estimates for the data gathered within our study.  
The cows were studied between May and August, since we had been monitoring physiological indicators and other parameters in May, when they are in comfort. Those parameters were subsequently being tracked during the warmer months, from June to August, in order to investigate the effect of heat stress on the physiological, productive and reproductive features. The reason for this is that the animals had not passed the long period of lactation at that time, and it can be argued that the changes in milk production and content, as well as in other indicators, are due to heat stress. Let us also point out that the experiments have been carried out under field conditions--not in a laboratory-controlled environment. We have chosen namely these features namely because they are easy to measure and are highly correlated with the rectal temperature, as Figures 2 and 3 illustrate. An estimate of their significance for the model is presented in the next section. The time of measurement is included as text or categorical data. As it turns out, this parameter carries crucial information due to the animals' daily physiological cycles and varying conditions in the farm. Neglecting it reduces our evaluation metric estimates drastically: in some cases, up to 50%.  
\begin{table}
\begin{tabular}{l c c c c} \hline
**Feature** & **Mode** & **Median** & **Mean** & **Standard Deviation** \\ \hline THI & 75.4 & 75.2 & 74.9 & 2.58 \\ Resp. & 9.0 & 10.0 & 10.8 & 3.11 \\ Pulse & 21.0 & 21.0 & 20.6 & 2.24 \\ R-temp. & 38.5 & 38.7 & 38.8 & 0.48 \\ \hline \end{tabular}
\end{table}
Table 1: Basic statistical indicators for the gathered data: 138 instances in sample A, 522 in sample B.  
Figure 2: Our tabular predictors against the measured rectal temperature for the two samples.