Create README.md

README.md

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+---
+language:
+- en
+license: other
+license_name: titanic-competition-license
+license_link: https://www.kaggle.com/competitions/titanic/data
+license_details: >-
+  This dataset is provided for use under the Titanic Machine Learning
+  competition rules.
+tags:
+- tabular
+- classification
+- survival-analysis
+- competition
+annotations_creators:
+- found
+language_creators:
+- found
+language_details: en-US
+pretty_name: 'Copy of the original Kaggle Titanic dataset '
+size_categories:
+- 1K<n<10K
+source_datasets:
+- found
+task_categories:
+- tabular-classification
+task_ids:
+- tabular-multi-class-classification
+paperswithcode_id: titanic-survival
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train.csv
+  - split: test
+    path: test.csv
+  - split: gender_submission
+    path: gender_submission.csv
+dataset_info:
+  features:
+  - name: PassengerId
+    dtype: int32
+  - name: Survived
+    dtype: int32
+  - name: Pclass
+    dtype: int32
+  - name: Name
+    dtype: string
+  - name: Sex
+    dtype: string
+  - name: Age
+    dtype: float32
+  - name: SibSp
+    dtype: int32
+  - name: Parch
+    dtype: int32
+  - name: Ticket
+    dtype: string
+  - name: Fare
+    dtype: float32
+  - name: Cabin
+    dtype: string
+  - name: Embarked
+    dtype: string
+  config_name: default
+  splits:
+  - name: train
+    num_bytes: 61194
+    num_examples: 891
+  - name: test
+    num_bytes: 28629
+    num_examples: 418
+  download_size: 93080
+  dataset_size: 89823
+extra_gated_fields:
+  Competition Agreement: checkbox
+extra_gated_prompt: >-
+  By accessing this dataset, you agree to abide by the competition rules and not
+  use external datasets for training.
+train-eval-index:
+- config: default
+  task: tabular-classification
+  task_id: tabular-multi-class-classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    features:
+    - Pclass
+    - Sex
+    - Age
+    - SibSp
+    - Parch
+    - Fare
+    - Embarked
+    label: Survived
+  metrics:
+  - type: accuracy
+    name: Accuracy
+dataset_details:
+  original_url: https://www.kaggle.com/competitions/titanic/data
+  description: >
+    This dataset is a **copy of the original Kaggle Titanic dataset** uploaded
+    for exploring the **Hugging Face Datasets feature**.
+
+    The Titanic dataset is a classic dataset used in machine learning and
+    statistics.
+
+    It consists of passenger information and survival status from the Titanic
+    disaster.
+
+    The dataset is provided as part of the Kaggle Titanic competition.
+---
+
+# Dataset Card for Titanic Survival Prediction
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset is a **copy of the original Kaggle Titanic dataset** made to explore the **Hugging Face Datasets feature**.
+
+The **Titanic Survival Prediction** dataset is widely used in machine learning and statistics. It originates from the **Titanic: Machine Learning from Disaster** competition on [Kaggle](https://www.kaggle.com/competitions/titanic/data). The dataset consists of passenger details from the RMS Titanic disaster, including demographic and ticket-related attributes, with the goal of predicting whether a passenger survived.
+
+- **Curated by:** Kaggle
+- **Funded by:** Kaggle
+- **Shared by:** Kaggle
+- **Language(s) (NLP, if applicable):** English
+- **License:** Subject to Competition Rules
+
+### Dataset Sources
+
+- **Repository:** [Kaggle Titanic Competition](https://www.kaggle.com/competitions/titanic/data)
+- **Paper [optional]:** None
+- **Demo [optional]:** Not applicable
+
+## Uses
+
+### Direct Use
+
+The dataset is primarily used for:
+- **Supervised learning**: Predicting survival outcomes based on passenger characteristics.
+- **Feature engineering**: Extracting new insights from existing features.
+- **Data preprocessing techniques**: Handling missing values, encoding categorical variables, and normalizing data.
+- **Benchmarking machine learning models**: Logistic regression, decision trees, random forests, neural networks, etc.
+
+### Out-of-Scope Use
+
+This dataset is not meant for:
+- **Real-world survival predictions**: It is based on a historical dataset and should not be used for real-world survival predictions.
+- **Sensitive or personally identifiable information analysis**: The dataset does not contain modern personal data but should still be used responsibly.
+
+## Dataset Structure
+
+The dataset consists of three CSV files:
+1. **train.csv** (891 entries) – Includes the "Survived" column as labels for training.
+2. **test.csv** (418 entries) – Used for evaluation, with missing "Survived" labels.
+3. **gender_submission.csv** – A sample submission file assuming all female passengers survived.
+
+### Data Dictionary
+
+| Column     | Description |
+|------------|------------|
+| PassengerId | Unique ID for each passenger |
+| Survived | Survival status (0 = No, 1 = Yes) |
+| Pclass | Ticket class (1st, 2nd, 3rd) |
+| Name | Passenger name |
+| Sex | Gender (male/female) |
+| Age | Passenger age |
+| SibSp | Number of siblings/spouses aboard |
+| Parch | Number of parents/children aboard |
+| Ticket | Ticket number |
+| Fare | Ticket fare |
+| Cabin | Cabin number (if known) |
+| Embarked | Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton) |
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was created to help users develop predictive models for classification tasks and serves as an entry-level machine learning dataset.
+
+### Source Data
+
+#### Data Collection and Processing
+
+The dataset originates from historical records of the RMS Titanic disaster and has been structured for machine learning purposes. Some entries contain missing values, particularly in **Age** and **Cabin**, requiring imputation or removal.
+
+#### Who are the source data producers?
+
+The dataset is derived from **Titanic passenger records**.
+
+### Annotations
+
+#### Annotation process
+
+The dataset is not annotated beyond the **Survived** label.
+
+#### Who are the annotators?
+
+The survival labels come from historical records.
+
+#### Personal and Sensitive Information
+
+The dataset does not contain sensitive or personally identifiable information.
+
+## Bias, Risks, and Limitations
+
+The dataset represents **historical biases** in survival rates:
+- Women and children had a higher chance of survival due to evacuation priorities.
+- First-class passengers had a higher survival rate compared to lower-class passengers.
+- Some data is **missing or estimated**, particularly age and cabin numbers.
+
+### Recommendations
+
+- **Use fairness metrics** when training models to assess potential biases.
+- **Avoid real-world applications** for decision-making, as this is a historical dataset.
+
+## Citation
+
+Since this dataset originates from Kaggle, it does not have an official citation. However, you can reference it as follows:
+
+**APA:**
+Kaggle. (n.d.). Titanic - Machine Learning from Disaster. Retrieved from [https://www.kaggle.com/competitions/titanic/data](https://www.kaggle.com/competitions/titanic/data)
+
+**BibTeX:**
+```bibtex
+@misc{kaggle_titanic,
+  title = {Titanic - Machine Learning from Disaster},
+  author = {Kaggle},
+  year = {n.d.},
+  url = {https://www.kaggle.com/competitions/titanic/data}
+}