Question

You're trying to predict whether it will rain on the day of your child's birthday party. The party is at a park. If it doesn't rain, then you can sit in the grass to eat. If it does rain, sitting in the grass will be very unpleasant, and you'd prefer to sit at the sheltered tables. But, the shelter costs $100 to reserve, and you have to decide 1 week ahead you can't just wait to see the actual weather before deciding. Assume you can't use the shelter if you don't reserve it. You quantify your loss in different scenarios as the loss function L(y,g), where y=1 if it actually rains and y=0 if not, and g is your guess: L(1,1)=L(0,0)=0, and L(0,1)=100, L(1,0)=500. Let P(Y=1)=0.1. Then, your optimal prediction is g=

Answer 1

Answer :

Optimal prediction of the majority outcome. because this is a classification problem. so we can use many classification algorithms to solve this such as logistic regression, SVM, gradient boosting classifier. In the final decision, we will make the decision based on the voting system. and for the regression, we take the decision by taking the simple average.

So in this example, we take the average of all the predicted outcomes to find the optimal predictions.

OPTIMAL PREDICTION =L+0+100+500\4