length_of_encounter_seconds <= 3150.0 entropy = 0.745 samples = 4165 value = [3282, 883]
latitude <= 40.872 entropy = 0.758 samples = 3882 value = [3032, 850]
latitude <= 48.496 entropy = 0.52 samples = 283 value = [250, 33]
latitude <= 33.717 entropy = 0.793 samples = 2492 value = [1897, 595]
latitude <= 41.642 entropy = 0.688 samples = 1390 value = [1135, 255]
longitude <= -119.993 entropy = 0.478 samples = 272 value = [244, 28]
longitude <= -134.017 entropy = 0.994
samples = 11 value = [6, 5]
entropy = 0.714 samples = 754 value = [606, 148]
entropy = 0.822 samples = 1738 value = [1291, 447]
entropy = 0.524 samples = 296 value = [261, 35]
entropy = 0.724 samples = 1094 value = [874, 220]
entropy = 0.0 samples = 25 value = [25, 0]
entropy = 0.51 samples = 247 value = [219, 28]
entropy = 0.0 samples = 5 value = [5, 0]
entropy = 0.65 samples = 6 value = [1, 5]
Figure 2: Model 2: Max Depth 3
Model 3: Predicting Day/Night using Latitude and Longitude (MAXDEPTH=10, entropy)
• Accuracy: 80.20% • Prediction for UW-Madison campus gives “Night”. • This shows that the encounter duration has little correlation with whether a UFO appears during Day/Night.
length_of_encounter_seconds <= 210.0 entropy = 3.791 samples = 4165
value = [117, 82, 101, 403, 10, 11, 81, 1, 62, 253, 34 305, 79, 141, 867, 307, 209, 67, 278, 27, 437, 293]
length_of_encounter_seconds <= 5.5 entropy = 3.803 samples = 2189 value = [40, 61, 53, 187, 2, 7, 47, 0, 27, 123, 17, 208 56, 63, 409, 177, 103, 44, 142, 11, 256, 156]
latitude <= 35.685 entropy = 3.734 samples = 1976 value = [77, 21, 48, 216, 8, 4, 34, 1, 35, 130, 17, 97 23, 78, 458, 130, 106, 23, 136, 16, 181, 137]
latitude <= 43.734 entropy = 3.764 samples = 453 value = [3, 10, 8, 39, 0, 2, 7, 0, 4, 18, 4, 67, 32 11, 72, 38, 22, 9, 34, 4, 43, 26]
longitude <= -121.302 entropy = 3.783 samples = 1736 value = [37, 51, 45, 148, 2, 5, 40, 0, 23, 105, 13, 141 24, 52, 337, 139, 81, 35, 108, 7, 213, 130]
latitude <= 34.153 entropy = 3.703 samples = 653 value = [33, 4, 10, 79, 0, 1, 6, 0, 17, 52, 4, 37, 14 21, 134, 53, 33, 4, 40, 6, 60, 45]
longitude <= -82.26 entropy = 3.723 samples = 1323 value = [44, 17, 38, 137, 8, 3, 28, 1, 18, 78, 13, 60 9, 57, 324, 77, 73, 19, 96, 10, 121, 92]
entropy = 3.737 samples = 360 value = [1, 8, 8, 28, 0, 2, 5, 0, 3, 15, 2, 46, 28, 6 63, 29, 22, 9, 27, 3, 38, 17]
entropy = 3.534 samples = 93 value = [2, 2, 0, 11, 0, 0, 2, 0, 1, 3, 2, 21, 4, 5 9, 9, 0, 0, 7, 1, 5, 9]
entropy = 3.548 samples = 214 value = [4, 5, 9, 15, 1, 0, 5, 0, 5, 13, 0, 21, 2, 2 55, 30, 5, 5, 3, 2, 16, 16]
entropy = 3.791 samples = 1522 value = [33, 46, 36, 133, 1, 5, 35, 0, 18, 92, 13, 120 22, 50, 282, 109, 76, 30, 105, 5, 197, 114]
entropy = 3.662 samples = 475 value = [24, 3, 6, 68, 0, 0, 5, 0, 15, 31, 4, 27, 10 16, 104, 34, 18, 4, 27, 5, 47, 27]
entropy = 3.659 samples = 178 value = [9, 1, 4, 11, 0, 1, 1, 0, 2, 21, 0, 10, 4, 5 30, 19, 15, 0, 13, 1, 13, 18]
entropy = 3.674 samples = 861 value = [35, 12, 22, 83, 3, 1, 24, 1, 9, 39, 8, 36, 9 43, 227, 49, 43, 8, 61, 6, 76, 66]
entropy = 3.737 samples = 462 value = [9, 5, 16, 54, 5, 2, 4, 0, 9, 39, 5, 24, 0 14, 97, 28, 30, 11, 35, 4, 45, 26]
Figure 3: Model 3: Max Depth 3
3.3 Logistic Regression 1. Studying the Relationship between Length of UFO Encounter and Time of Day (Day or Night) • Divided data into Training, Validation, and Testing.
• Training the Logistic Regression Model. • Intercept and slope of the logistic equation:
intercept = -1.40938652 slope = -3.32652752e 08
3
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