Ice cream consumption exhibits a seasonal pattern, higher during warmer seasons like spring and summer, and lower during colder seasons like autumn and winter. The season variable categorises the seasons as follows: 1 = spring, 2 = summer, 3 = autumn, and 4 = winter. Our objective is to predict the season based on external factors such as temperature, price, and the presence of a holiday or special event (represented by the 'events holidays' variable, where 1 indicates an event/holiday and 0 indicates no event/holiday). In the resulting classification tree, each node represents a split based on one of the predictor variables. 2 1 31 26 26 17 84% events_holidays >= 0.5 1. 3 26 26 34 14 100% yes price < 4.4 no 2 26 32 26 15 68% temperature < 14 22 2 ETI 30 30 22 19 54% price >= 2 1 2 3 3 50 .00 25 25 14 43 43 .00 32 42 .16.11 25 00 38 38 00 25 75 00 16% 14% 38% 16% 16% What do each node's decimal numbers and percentage values represent? Please provide a concise explanation, taking the first split of a tree branch as an example.