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Problem · Array

K-Capable Model Costs

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Problem statement

There are n machine learning models. Model i has cost cost[i] and a two-character string featureAvailability[i]:

"00": supports neither feature.
"01": supports Feature B only.
"10": supports Feature A only.
"11": supports both Feature A and Feature B.

A selected set of models is k-capable if at least k selected models support Feature A and at least k selected models support Feature B. A "11" model counts toward both totals.

For every k from 1 to n, return the minimum total cost needed to choose a k-capable set. If no such set exists, return -1 for that k.

Return a long[] containing the answers for k = 1 through n.

Function

getMinimumModelCosts(cost: int[], featureAvailability: String[]) → long[]

Examples

Example 1

cost = [3,2,5,4]featureAvailability = ["10","01","11","00"]return = [5,10,-1,-1]

For k = 1, either the dual-feature model or the two single-feature models cost 5. For k = 2, the first three useful models cost 10. Larger values of k are impossible.

Example 2

cost = [8,1,2,6]featureAvailability = ["11","10","01","11"]return = [3,9,17,-1]

For k = 1, pair the models costing 1 and 2. For k = 2, also choose the dual-feature model costing 6. For k = 3, all four models are required. The value k = 4 is impossible.

Constraints

1 <= n <= 10^5
1 <= cost[i] <= 10^9
featureAvailability[i] is one of "00", "01", "10", or "11".