Data and Datasets

Data and datasets provide the examples used to develop machine-learning models. Data is organized into a dataset, where each example may contain a feature and, for supervised learning, a label.

Japanese terms

1. Data and datasets — データとデータセット: The examples and organized collections used for analysis and machine learning.
2. Data — データ: Recorded observations, measurements, symbols, or examples used for analysis and learning.
3. Dataset — データセット: An organized collection of related data used for analysis or model development.
4. Feature — 特徴量とくちょうりょう: A measurable input property supplied to a machine-learning model.
5. Label — ラベル: A known category or target attached to an example in labeled data.

Related topics

Training, validation, and testing explains how datasets are partitioned during model development.