a guest Jan 23rd, 2019 67 Never
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- import numpy as np
- from sklearn import linear_model
- class MarketingCosts:
- # param marketing_expenditure list. Expenditure for each previous campaign.
- # param units_sold list. The number of units sold for each previous campaign.
- # param desired_units_sold int. Target number of units to sell in the new campaign.
- # returns float. Required amount of money to be invested.
- def desired_marketing_expenditure(marketing_expenditure, units_sold, desired_units_sold):
- regr = linear_model.LinearRegression()
- regr.fit(u_sold, mar_exp)
- return round(pred,1)
- #For example, with the parameters below the function should return 250000.0.
- [300000, 200000, 400000, 300000, 100000],
- [60000, 50000, 90000, 80000, 30000],
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