README.md

metadata

dataset_info:
  features:
    - name: phone_hours
      dtype: float64
    - name: computer_hours
      dtype: float64
    - name: device_count
      dtype: int64
    - name: sleep_quality
      dtype: string
    - name: use_before_bed
      dtype: int64
    - name: sleep_time
      dtype: int64
    - name: sleep_hours
      dtype: float64
  splits:
    - name: original
      num_bytes: 1697
      num_examples: 30
    - name: augmented
      num_bytes: 16964
      num_examples: 300
  download_size: 8644
  dataset_size: 18661
configs:
  - config_name: default
    data_files:
      - split: original
        path: data/original-*
      - split: augmented
        path: data/augmented-*

Dataset Summary

This dataset records daily electronic device usage and sleep patterns of students.
It is designed for exploring the relationship between screen time, device behavior, and average sleep duration.

• Original size: 30 samples
• Augmented size: 300 samples
• Task type: Regression (predicting daily sleep hours)
• Goal: Predict sleep_hours from usage and sleep-related features

Data Splits

• No fixed train/test split is provided.
• Users can apply their own strategy (e.g., 80/20 split).

Intended Uses

• Regression Task: Predict sleep_hours from device usage.
• Correlation Analysis: Study relationships between screen time and sleep quality.
• Education: Demonstrates dataset augmentation (30 → 300 samples).