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Titanic Zero Prediction Model
Data Science and Analytics
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About
This dataset offers a Titanic baseline model submission file, meticulously crafted as an 'all zeros' CSV. It serves as a fundamental reference point, establishing a worst-case performance benchmark for any models developed with Titanic data. Achieving a leaderboard score of 0.62200, this file is essential for comparison; any model that fails to exceed this score is likely experiencing significant issues. The dataset is a standard Titanic submission file where all 'Survived' entries are uniformly set to zero, corresponding to the majority class.
Columns
- PassengerId: This column is used to identify each individual passenger. It consists of 418 valid entries, with no mismatched or missing values, and its label counts span from 892.00 to 1309.00. The mean value is approximately 1.1k, accompanied by a standard deviation of 121. The quantiles range from a minimum of 892, a 25th percentile of 996, a median of 1101, a 75th percentile of 1205, to a maximum of 1309.
- Survived: This column denotes the survival prediction. Within this baseline dataset, all 418 valid entries are consistently set to 0, signifying a uniform prediction of 'not survived' for every passenger. There are no mismatched or missing values. The mean, standard deviation, and all quantile values for this column are identically 0.
Distribution
The dataset is presented as a CSV file, specifically named
all_0s.csv, with a modest file size of 3.26 kB. Its structure adheres to that of a conventional Titanic submission file, containing 418 individual records.Usage
This dataset is perfectly suited for benchmarking and model evaluation within the context of the Titanic survival prediction challenge. Its key applications include:
- Facilitating the comparison of new machine learning models against a defined minimum performance standard.
- Helping to pinpoint underperforming models that do not surpass this basic benchmark.
- Acting as an educational resource to illustrate the concept and importance of baseline models in data science practices.
Coverage
This dataset represents a synthetic baseline tailored for the Titanic survival prediction task. It does not inherently contain direct geographic, time range, or demographic scope information; instead, it provides a prediction output for the entire set of Titanic passengers. As a static file, it does not account for data availability differences across various groups or over time.
License
CC0: Public Domain
Who Can Use It
This baseline model dataset is invaluable for:
- Data scientists and machine learning engineers seeking to rapidly assess the initial efficacy of their predictive models.
- Researchers and academics who utilise the Titanic dataset for experimental designs and scholarly publications.
- Students engaged in learning about classification, model assessment, and the establishment of baselines in their data science curricula.
- Any participant in the Kaggle Titanic competition requiring a straightforward, yet fundamental, performance benchmark.
Dataset Name Suggestions
- Titanic All-Zeros Baseline
- Titanic Zero Prediction Model
- Titanic Benchmark Submission
- Worst-Case Titanic Predictor
- Titanic Majority Class Baseline
Attributes
Original Data Source Link: Titanic Zero Prediction Model
QUALITY