dodatkowe dane
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9ebac46bef
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248
Data/dataTree2.csv
Normal file
248
Data/dataTree2.csv
Normal file
@ -0,0 +1,248 @@
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plant_water_level,growth,disease,fertility,tractor_water_level,temperature,rain,season,current_time,action
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1,20,0,40,60,2,0,2,1,1
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20,40,0,40,60,2,0,2,1,1
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87,20,0,40,60,2,0,2,1,0
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27,43,1,40,60,2,0,2,1,0
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89,56,1,40,60,2,1,1,1,0
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67,100,1,37,55,1,3,3,3,0
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67,40,1,87,90,4,0,1,0,0
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1,20,0,40,60,2,0,0,1,0
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20,40,0,40,60,2,0,0,1,0
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87,20,0,56,45,2,0,0,2,0
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27,43,1,40,60,2,0,0,3,0
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89,56,1,40,89,2,1,0,1,0
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67,100,1,37,55,1,3,0,3,0
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67,40,1,87,90,4,0,0,0,0
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1,100,0,45,20,2,0,2,1,0
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20,100,0,40,34,0,1,2,0,0
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87,100,0,56,60,2,0,1,1,0
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27,100,0,89,67,1,2,2,2,0
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89,100,0,40,60,2,1,1,1,0
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76,100,0,37,55,1,3,3,3,0
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67,100,0,87,90,4,0,1,0,0
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1,20,0,40,0,2,0,2,1,0
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20,40,0,40,0,2,0,2,1,0
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87,20,0,40,0,2,0,2,1,0
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27,43,1,40,0,2,0,2,1,0
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89,56,1,40,0,2,1,1,1,0
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67,100,1,37,0,1,3,3,3,0
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67,40,1,87,0,4,0,1,0,0
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1,20,0,40,0,2,0,0,1,0
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20,40,0,40,0,2,0,0,1,0
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87,20,0,56,0,2,0,0,2,0
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27,43,1,40,0,2,0,0,3,0
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89,56,1,40,0,2,1,0,1,0
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67,100,1,37,0,1,3,0,3,0
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67,40,1,87,0,4,0,0,0,0
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1,100,0,45,0,2,0,2,1,0
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20,100,0,40,0,0,1,2,0,0
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87,100,0,56,0,2,0,1,1,0
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27,100,0,89,0,1,2,2,2,0
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89,100,0,40,0,2,1,1,1,0
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76,100,0,37,0,1,3,3,3,0
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67,100,0,87,0,4,0,1,0,0
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1,45,0,56,44,2,1,1,1,1
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20,55,0,43,34,2,0,2,2,1
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15,23,0,23,26,2,1,3,3,1
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45,67,0,12,67,3,0,1,0,1
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59,88,0,34,87,3,0,2,1,1
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32,32,0,32,90,3,0,3,2,1
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44,43,0,19,27,2,0,1,3,1
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33,11,0,28,76,2,0,2,0,1
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54,90,0,44,5,3,0,3,1,1
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21,76,0,50,25,3,1,1,2,1
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29,64,0,38,36,2,0,2,3,1
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11,54,0,65,44,3,1,1,2,1
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23,55,0,34,43,3,0,2,1,1
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51,32,0,32,62,3,1,3,3,1
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54,76,0,21,76,2,0,1,2,1
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95,88,0,43,78,2,0,2,1,0
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23,23,0,23,9,2,0,3,3,1
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44,34,0,91,72,3,0,1,0,1
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33,11,0,82,67,3,0,2,2,1
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45,9,0,44,50,2,0,3,3,1
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21,67,0,50,52,2,1,1,0,1
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92,46,0,83,63,3,0,2,1,0
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20,55,1,43,34,0,0,2,2,0
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15,23,1,23,26,0,1,3,3,0
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45,67,1,12,67,0,0,1,0,0
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59,88,1,34,87,0,0,2,1,0
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32,32,0,32,90,0,0,3,2,0
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44,43,0,19,27,4,0,1,3,0
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33,11,0,28,76,4,0,2,0,0
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54,90,0,44,5,4,0,3,1,0
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21,76,0,50,25,4,1,1,2,0
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29,64,0,38,36,4,0,2,3,0
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11,54,0,65,44,0,1,1,2,0
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23,55,0,34,43,0,0,2,1,0
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51,32,0,32,62,0,1,3,3,0
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80,76,1,39,7,3,0,1,0,0
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98,77,0,15,91,1,3,2,3,0
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3,48,1,73,41,2,2,0,3,0
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20,15,1,97,87,4,1,2,1,0
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93,6,0,37,0,0,1,0,1,0
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4,31,0,1,5,2,3,1,2,0
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42,52,0,33,19,3,2,3,0,0
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76,43,0,77,18,4,0,0,3,0
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31,13,1,21,42,0,1,2,3,0
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96,65,1,63,35,1,3,3,2,0
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29,39,0,40,37,3,3,0,0,0
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82,53,0,55,9,0,1,3,2,0
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21,35,0,58,1,1,2,2,0,0
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92,98,0,69,16,3,0,0,1,0
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34,23,0,95,2,2,3,0,3,0
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36,28,0,62,22,0,1,1,1,0
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66,88,1,10,85,3,1,2,3,0
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53,51,0,79,90,2,2,3,2,0
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9,74,0,60,4,4,1,2,3,1
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17,0,0,38,58,1,2,3,0,0
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12,76,0,50,25,3,1,1,2,1
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92,64,0,38,36,2,0,2,3,0
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11,54,0,65,44,3,1,1,2,1
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32,55,0,34,43,3,0,2,1,1
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15,32,0,32,62,3,1,3,3,1
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45,76,0,21,76,2,0,1,2,1
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59,88,0,43,78,2,0,2,1,1
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32,23,0,23,9,2,0,3,3,1
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14,34,0,91,72,3,0,1,0,1
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13,11,0,82,67,3,0,2,2,1
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45,9,0,44,50,2,0,3,3,1
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21,67,0,50,52,2,1,1,0,1
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92,46,0,83,63,3,0,2,1,0
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2,40,1,34,43,1,3,2,2,0
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51,32,1,32,62,2,1,3,3,0
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54,76,1,21,76,3,0,1,0,0
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98,38,0,50,44,4,0,1,0,0
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63,7,0,93,79,2,0,2,1,1
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91,59,0,94,24,4,0,3,2,0
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11,49,0,54,76,2,0,1,3,1
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33,31,0,59,39,3,0,1,3,1
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28,50,0,26,0,4,0,2,2,0
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54,83,0,36,0,3,0,2,1,0
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49,78,0,68,0,2,0,3,2,0
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59,21,0,43,100,1,0,3,2,1
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1,30,0,52,100,2,0,0,3,0
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60,9,0,40,40,3,0,0,3,0
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85,94,0,87,85,4,0,1,3,0
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79,68,0,56,90,1,0,2,2,1
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75,22,0,25,95,1,0,3,2,1
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100,51,0,33,12,0,0,2,2,0
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90,70,0,71,81,0,0,2,1,0
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47,26,0,6,78,4,0,1,1,1
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14,89,0,70,18,4,0,1,0,1
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99,19,0,74,91,2,0,3,0,0
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18,48,0,15,32,2,0,3,0,1
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5,57,0,14,34,0,1,1,3,1
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22,67,0,9,5,0,1,2,2,0
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95,81,0,46,86,1,1,3,1,0
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39,65,0,84,0,1,1,0,0,0
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84,75,0,30,0,2,1,1,1,0
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86,41,0,2,67,2,1,2,2,0
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64,53,0,53,47,1,1,3,3,1
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69,61,0,0,73,2,1,0,0,0
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94,40,1,0,18,3,1,1,2,0
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62,82,1,20,50,4,1,2,3,0
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57,1,1,17,92,0,1,3,2,0
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80,35,1,58,45,0,0,3,1,0
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30,47,1,8,47,1,0,2,1,0
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82,32,0,99,39,1,3,1,3,0
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20,84,0,0,51,2,3,2,3,0
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42,88,0,0,54,2,2,2,0,0
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66,45,0,91,10,3,2,1,0,0
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81,14,0,19,55,3,0,1,2,1
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74,37,0,88,78,4,0,3,2,1
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89,99,0,100,60,4,0,3,3,0
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15,20,0,45,11,0,0,1,3,1
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92,28,0,85,90,2,0,1,1,0
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55,4,0,13,95,2,0,2,1,1
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2,6,0,35,0,2,0,2,0,0
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61,56,0,90,0,2,0,3,0,0
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76,11,0,61,10,3,0,3,1,1
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26,80,0,57,9,3,0,1,2,1
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40,44,0,81,8,3,0,2,3,1
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50,66,0,23,7,3,0,3,0,1
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48,15,0,77,6,2,0,0,1,0
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11,54,0,65,44,3,3,1,2,0
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23,55,0,34,43,3,3,2,1,0
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51,32,0,32,62,3,3,3,3,0
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54,76,0,21,76,2,3,1,2,0
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95,88,0,43,78,2,3,2,1,0
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23,23,0,23,9,2,3,3,3,0
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44,34,0,91,72,3,3,1,0,0
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33,11,0,82,67,3,3,2,2,0
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45,9,0,44,50,2,3,3,3,0
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21,67,0,50,52,2,3,1,0,0
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92,46,0,83,63,3,3,2,1,0
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20,55,1,43,34,0,3,2,2,0
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15,23,1,23,26,0,3,3,3,0
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45,67,1,12,67,0,3,1,0,0
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59,88,1,34,87,0,3,2,1,0
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32,32,0,32,90,0,3,3,2,0
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1,60,0,55,11,0,1,0,0,1
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2,70,0,44,12,1,1,0,1,1
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3,44,0,11,13,2,1,0,2,1
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4,55,0,34,66,3,0,0,3,1
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5,66,0,90,77,0,0,1,2,1
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6,22,0,89,88,0,0,2,2,1
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7,1,0,45,9,0,1,2,3,1
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8,2,0,34,22,3,1,2,3,1
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9,3,0,56,34,3,1,0,1,1
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10,6,0,78,5,3,0,3,1,1
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11,8,0,36,67,2,0,0,0,1
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12,59,0,57,23,2,1,1,0,1
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13,67,0,29,34,1,1,0,1,1
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14,20,0,30,90,1,1,2,2,1
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15,21,0,66,89,0,1,3,3,1
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44,100,0,91,72,3,3,1,0,0
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33,100,0,82,67,3,3,2,2,0
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45,100,0,44,50,2,3,3,3,0
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21,100,0,50,52,2,3,1,0,0
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92,100,0,83,63,3,3,2,1,0
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20,100,1,43,34,0,3,2,2,0
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15,100,1,23,26,0,3,3,3,0
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45,100,1,12,67,0,3,1,0,0
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59,100,1,34,87,0,3,2,1,0
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32,100,0,32,90,0,3,3,2,0
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1,100,0,55,11,0,1,0,0,0
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2,100,0,44,12,1,1,0,1,0
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3,100,0,11,13,2,1,0,2,0
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4,100,0,34,66,3,0,0,3,0
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5,100,0,90,77,0,0,1,2,0
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6,100,0,89,88,0,0,2,2,0
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7,100,0,45,9,0,1,2,3,0
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8,100,0,34,22,3,1,2,3,0
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9,100,0,56,34,3,1,0,1,0
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10,100,0,78,5,3,0,3,1,0
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11,100,0,36,67,2,0,0,0,0
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12,100,0,57,23,2,1,1,0,0
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13,100,0,29,34,1,1,0,1,0
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14,100,0,30,90,1,1,2,2,0
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15,100,0,66,89,0,1,3,3,0
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1,6,0,5,10,4,1,1,3,1
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2,7,0,4,20,4,1,2,2,1
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3,4,0,11,30,4,1,3,1,1
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4,5,0,43,5,2,0,1,2,1
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5,6,0,9,17,2,0,2,1,1
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6,2,0,98,18,4,0,3,1,1
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7,11,0,54,19,4,1,0,2,1
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8,20,0,43,22,4,1,1,1,1
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9,30,0,65,43,4,1,2,3,1
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10,60,0,87,50,1,0,3,3,1
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11,80,0,63,76,1,0,0,2,1
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12,95,0,75,32,1,1,1,1,1
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13,76,0,30,43,2,1,2,0,1
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14,2,0,92,9,2,1,3,0,1
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1,6,0,5,10,4,3,1,3,0
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2,7,0,4,20,4,3,2,2,0
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3,4,0,11,30,4,3,3,1,0
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4,5,0,43,5,2,3,1,2,0
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5,6,0,9,17,2,3,2,1,0
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6,2,0,98,18,4,3,3,1,0
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7,11,0,54,19,4,3,0,2,0
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8,20,0,43,22,4,3,1,1,0
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9,30,0,65,43,4,3,2,3,0
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10,60,0,87,50,1,3,3,3,0
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11,80,0,63,76,1,3,0,2,0
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12,95,0,75,32,1,3,1,1,0
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13,76,0,30,43,2,3,2,0,0
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14,2,0,92,9,2,3,3,0,0
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@ -9,6 +9,7 @@ class Drzewo:
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def treeLearn(self):
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csvdata=pandas.read_csv('Data/dataTree.csv')
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#csvdata = pandas.read_csv('Data/dataTree2.csv')
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x=csvdata[atributes]
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decision=csvdata['action']
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self.tree=skltree.DecisionTreeClassifier()
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