**Objective**

In this challenge, we practice using *multiple linear regression*. Check out the Tutorial tab for learning materials!

**Task**

Andrea has a simple equation:

**Note:** You are not expected to account for bias and variance trade-offs.

**Input Format**

The first line contains space-separated integers, (the number of observed features) and (the number of feature sets Andrea studied), respectively.

Each of the subsequent lines contain space-separated decimals; the first elements are features , and the last element is the value of for the line's feature set.

The next line contains a single integer, , denoting the number of feature sets Andrea wants to query for.

Each of the subsequent lines contains space-separated decimals describing the feature sets.

**Constraints**

**Scoring**

For each feature set in one test case, we will compute the following:

- . We will permit up to a margin of error.

The normalized score for each test case will be: . If the challenge is worth points, then your score will be .

**Output Format**

For each of the feature sets, print the value of on a new line (i.e., you must print a total of lines).

**Sample Input**

```
2 7
0.18 0.89 109.85
1.0 0.26 155.72
0.92 0.11 137.66
0.07 0.37 76.17
0.85 0.16 139.75
0.99 0.41 162.6
0.87 0.47 151.77
4
0.49 0.18
0.57 0.83
0.56 0.64
0.76 0.18
```

**Sample Output**

```
105.22
142.68
132.94
129.71
```

**Explanation**

We're given , so . We're also given , so we determine that Andrea studied the following feature sets:

We use the information above to find the values of , , and . Then, we find the value of for each of the feature sets.