What is the quantity sold for a specific fruit & country combination?
What is the algorithm that generates these potential quantities that meet the given criteria?
Essentially - there are number of quantities for a fruit and country combination. E.g:
Country+Fruit Potential Quantity
1 India+Apple 25
2 India+Apple 27
3 India+Banana 35
4 India+Banana 37
5 France+Apple 130
6 France+Apple 132
7 France+Banana 11
8 France+Banana 13
9 France+Banana 15
10 France+Cherry 88
For complete dataset click here.
Each Country has to be as close as possible to the following values for all fruits sold:
Country Total Fruits Sold
1. Total India Fruits 1403
2. Total China Fruits 1370
3. Total England Fruits 1115
4. Total France Fruits 1169
5. Total Germany Fruits 1470
And total fruit quantity across all countries has to be as close as possible to the following values:
Fruits Total Fruits Sold Across All Countries:
1. Total Apples 508
2. Total Bananas 253
3. Total Cherries 982
4. Total Guavas 389
5. Total Kiwis 681
6. Total Oranges 489
7. Total Mangos 608
8. Total Strawberries 1060
An example combination that comes close to meeting the above criteria (having 5 countries and 8 fruits) is:
Country Fruits Matched Combination
1. India Mango 120
2. India Apple 40
3. Germany Apple 20
4. Germany Mango 80
.
.
40. France Mango 186
What is the algorithm that generates these potential quantities that meet this criterion?
Problem 1: do we have to do a brute force method of generating all possible combinations or is there a more efficient way?
Problem 2: how do we define "closeness" - the exact match is the best - what if there is no exact match - then what is the next best option?
Topic probabilistic-programming statistics data-mining machine-learning
Category Data Science