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--- |
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dataset_info: |
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features: |
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- name: phone_hours |
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dtype: float64 |
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- name: computer_hours |
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dtype: float64 |
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- name: device_count |
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dtype: int64 |
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- name: sleep_quality |
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dtype: string |
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- name: use_before_bed |
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dtype: int64 |
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- name: sleep_time |
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dtype: int64 |
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- name: sleep_hours |
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dtype: float64 |
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splits: |
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- name: original |
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num_bytes: 1697 |
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num_examples: 30 |
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- name: augmented |
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num_bytes: 16964 |
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num_examples: 300 |
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download_size: 8644 |
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dataset_size: 18661 |
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configs: |
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- config_name: default |
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data_files: |
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- split: original |
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path: data/original-* |
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- split: augmented |
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path: data/augmented-* |
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--- |
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## Dataset Summary |
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This dataset records **daily electronic device usage** and **sleep patterns** of students. |
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It is designed for exploring the relationship between screen time, device behavior, and **average sleep duration**. |
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- **Original size:** 30 samples |
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- **Augmented size:** 300 samples |
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- **Task type:** Regression (predicting daily sleep hours) |
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- **Goal:** Predict `sleep_hours` from usage and sleep-related features |
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## Data Splits |
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- No fixed train/test split is provided. |
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- Users can apply their own strategy (e.g., 80/20 split). |
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## Intended Uses |
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- **Regression Task:** Predict `sleep_hours` from device usage. |
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- **Correlation Analysis:** Study relationships between screen time and sleep quality. |
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- **Education:** Demonstrates dataset augmentation (30 → 300 samples). |
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