WEBVTT 00:00:00.600 --> 00:00:01.940 Now let's do an example. 00:00:01.940 --> 00:00:06.740 So here's your reminder of the formula and suppose this is my data. 00:00:06.740 --> 00:00:11.040 I have four data points and for each data point I have three features, 00:00:11.040 --> 00:00:17.570 the grade of the train, the bumpiness, whether there's a speed limit, 00:00:17.570 --> 00:00:20.709 and then the speed that the car goes. 00:00:21.950 --> 00:00:23.440 And i'm just making up some data here. 00:00:23.440 --> 00:00:26.890 So let's start out at the top of the decision tree here. 00:00:26.890 --> 00:00:31.960 So I have two slow examples and two fast examples. 00:00:31.960 --> 00:00:36.200 Slow, slow, fast, fast. 00:00:36.200 --> 00:00:39.199 So the first question is, what's the entropy of this node? 00:00:40.470 --> 00:00:42.590 So let's do this piece by piece. 00:00:42.590 --> 00:00:46.880 How many of the examples in this node are slow? 00:00:46.880 --> 00:00:47.810 Write your answer here.