문제
Models need numbers, not words. One-hot encoding turns each category into a vector with one position per category: 1 at the category's position and 0 everywhere else.
Order the categories alphabetically. For each label, output its one-hot vector.
Implement one_hot(labels).
Input
labels: A list of category names.
Output
Return a matrix with one row per label and one column per distinct category (alphabetical order).
제약 조건
1 ≤ length ≤ 1,000
Each label is 1 to 20 characters
예시
예시 1
입력:
labels = ["red", "green", "blue", "green"]
예상 출력:
expected = [
[0, 0, 1],
[0, 1, 0],
[1, 0, 0],
[0, 1, 0]
]입력:
std::vector<std::string> labels = {"red", "green", "blue", "green"};
예상 출력:
std::vector<std::vector<long long>> expected = {
{0, 0, 1},
{0, 1, 0},
{1, 0, 0},
{0, 1, 0}
};입력:
string[] labels = new string[] {"red", "green", "blue", "green"};
예상 출력:
long[][] expected = new long[][] {
new long[] {0, 0, 1},
new long[] {0, 1, 0},
new long[] {1, 0, 0},
new long[] {0, 1, 0}
};설명
The categories in alphabetical order are blue, green, red. So red → [0, 0, 1], green → [0, 1, 0] and blue → [1, 0, 0].
예시 2
입력:
labels = ["yes"]
예상 출력:
expected = [
[1]
]입력:
std::vector<std::string> labels = {"yes"};
예상 출력:
std::vector<std::vector<long long>> expected = {
{1}
};입력:
string[] labels = new string[] {"yes"};
예상 출력:
long[][] expected = new long[][] {
new long[] {1}
};설명
There is only one category, so every vector is [1].
참고 자료
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