3. Prediction for UW-Madison Campus.
clf.predict(np.array([[43.0766, 89.4125]])) #0:night, 1:day >>> array([0])
3.2 Decision Tree
Model 1: Predicting Day/Night using Latitude, Longitude, and Encounter Length
• Accuracy: 80.02% • Prediction for UW-Madison campus gives “Night” for all durations. • Decision trees excel in classifying fewer features.
latitude <= 40.808 entropy = 0.745 samples = 4165 value = [3282, 883]
latitude <= 33.717 entropy = 0.778 samples = 2671 value = [2056, 615]
latitude <= 41.633 entropy = 0.679 samples = 1494 value = [1226, 268]
latitude <= 21.311 entropy = 0.702 samples = 810 value = [656, 154]
longitude <= -111.87 entropy = 0.808 samples = 1861 value = [1400, 461]
longitude <= -81.891 entropy = 0.526 samples = 320 value = [282, 38]
latitude <= 42.28 entropy = 0.714 samples = 1174 value = [944, 230]
entropy = 0.996 samples = 13 value = [7, 6]
entropy = 0.692 samples = 797 value = [649, 148]
entropy = 0.879 samples = 483 value = [339, 144]
entropy = 0.778 samples = 1378 value = [1061, 317]
entropy = 0.275 samples = 190 value = [181, 9]
entropy = 0.766 samples = 130 value = [101, 29]
entropy = 0.821 samples = 207 value = [154, 53]
entropy = 0.687 samples = 967 value = [790, 177]
Figure 1: Model 1: Max Depth 3
Model 2: Predicting UFO Shape using Latitude and Longitude and Length of Encounter (MAXDEPTH=10, entropy) • Accuracy: 19.28% • Prediction for UW-Madison campus UFO Shape gives “Light” for all durations. • UFO Shapes are extremely random compared to Day/Night. Further investigation may be required to improve its performance.
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