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One-Hot Encoding

Turn categories into vectors with a single 1, the input format for classifiers and embeddings.

このチャレンジで学べること

  • Map categories to vector positions
  • Build one-hot rows for each label
  • Prepare categorical data for models

問題

翻訳を表示

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).

制約

1 ≤ length ≤ 1,000

Each label is 1 to 20 characters

例

例 1
入力:
labels = ["red", "green", "blue", "green"]

期待される出力:
expected = [
    [0, 0, 1],
    [0, 1, 0],
    [1, 0, 0],
    [0, 1, 0]
]
入力:
std::vector<std::string> labels = {"red", "green", "blue", "green"};

期待される出力:
std::vector<std::vector<long long>> expected = {
    {0, 0, 1},
    {0, 1, 0},
    {1, 0, 0},
    {0, 1, 0}
};
入力:
string[] labels = new string[] {"red", "green", "blue", "green"};

期待される出力:
long[][] expected = new long[][] {
    new long[] {0, 0, 1},
    new long[] {0, 1, 0},
    new long[] {1, 0, 0},
    new long[] {0, 1, 0}
};

解説

The categories in alphabetical order are blue, green, red. So red → [0, 0, 1], green → [0, 1, 0] and blue → [1, 0, 0].

例 2
入力:
labels = ["yes"]

期待される出力:
expected = [
    [1]
]
入力:
std::vector<std::string> labels = {"yes"};

期待される出力:
std::vector<std::vector<long long>> expected = {
    {1}
};
入力:
string[] labels = new string[] {"yes"};

期待される出力:
long[][] expected = new long[][] {
    new long[] {1}
};

解説

There is only one category, so every vector is [1].

参考資料

この課題はCodeUtility用に調整されています。上記の説明と制約に従ってください。

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