The Malaysian Railway Consortium have been trialling 2 different machine learning methods which attempt to predict wheth

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The Malaysian Railway Consortium Have Been Trialling 2 Different Machine Learning Methods Which Attempt To Predict Wheth 1 (61.79 KiB) Viewed 7 times

The Malaysian Railway Consortium have been trialling 2 different machine learning methods which attempt to predict whether a train will arrive at its destination on time or not, using several input features corresponding to weather conditions, train priorities, ongoing repair works etc. (for this purpose, 'on time' is defined as the train arriving no more than 10 minutes after its scheduled time). Two different machine learning methods have been tested on a common set of 500 train runs, and the results are as follows: Method Method 1 predicted on time Method 1 predicted late Method 2 predicted on time Method 2 predicted late i. ii. iii. Actually on time 131 19 82 68 Actually late 155 195 72 278 Total predictions 286 214 154 346 Compute the F₁ score for Method 1 and Method 2 for the trains being on time. (4 marks) Based on the F₁ score for Method 1 and Method 2, determine which of the method is the best method for the task. (1 mark) Explain the concept of precision and recall using the train prediction problem. (7 marks)