An insurance company is evaluating house insurance premiums for the next year in a given area. The company collects data on three features: Feature 1: Age - The age of the house in years. Feature 2: Size - The number of rooms in the house. Feature 3: Crime rate - This is an indicator for the average crime rate in the area. The company evaluates a sample of 800 houses in the area. Company's analyst uses linear programming to learn aggregation weights associated with a weighted arithmetic mean, OW OWA, a weighted power mean (p=0.5) and the Choquet integral. The analyst also calculate the arithmetic mean for comparison. The data were transformed to show that high score should be associated with high premium. All variables are transformed to [0,1] interval. The following results are obtained: