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Global Feline Insights for AI Innovation
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About
Street cat observations across diverse global regions provide a vital foundation for developing and testing artificial intelligence models. By documenting feline health, living conditions, and physical attributes, this resource enables researchers to unlock insights into urban animal welfare and habitat dynamics. It is designed to facilitate both the training and evaluation phases of machine learning projects, offering a structured approach to feline data analysis and innovation.
Columns
- Cat ID: A unique numerical identifier assigned to each individual cat.
- Country: The nation where the cat was located at the time of data collection.
- City: The specific urban area or city where the cat was found.
- Gender: The biological sex of the cat, recorded as Male or Female.
- Age: The age of the feline in years.
- Breed: The specific breed or mix of breeds identified.
- Weight (kg): The weight of the cat measured in kilogrammes.
- Color: The predominant colour or pattern of the cat's coat.
- Sterilization/Birth Control Status: Indicates whether the animal has been neutered or spayed.
- Health Condition: A general assessment of the cat's health, such as "Sick" or "Relatively" healthy.
- Immunization Program Participation: Records whether the cat is part of a vaccination or immunisation scheme.
- Feeding Type: The category of nutrition the cat receives, such as kibble or home-cooked food.
- Food Brand: The specific brand of food consumed by the animal.
- Human Interaction: The level of social engagement the cat has with people.
- Animal Rights Foundation Name: The name of the charity or foundation associated with the cat's care.
- Street Lifespan (in months): The known or estimated duration the cat has lived in an outdoor environment.
Distribution
The material is delivered in a structured CSV format consisting of two primary files:
train.csv with 400 entries and test.csv containing 25 entries. The test file has a size of approximately 3.99 kB. The data maintains a high usability rating of 10.00 and is expected to be updated on a weekly basis to ensure the information remains current for researchers.Usage
This resource is intended for use in various machine learning tasks, including classification, clustering, and regression analyses. It is ideal for predicting feline health outcomes, identifying patterns in urban cat populations, or understanding how environmental factors impact well-being. Researchers can use the separate training and testing files to build and validate robust predictive models.
Coverage
The geographic scope is global, with specific records originating from diverse locations including India and Portugal. The demographic focus is on street-dwelling felines, covering both male and female genders, ages ranging from 1 to 6 years, and various breeds such as Mixed Breed and Domestic Shorthair. The data captures a wide array of physical and environmental attributes, providing a thorough snapshot of street cat populations.
License
CC BY-NC-SA 4.0
Who Can Use It
Artificial intelligence researchers and machine learning enthusiasts can use these records to develop and benchmark new algorithms. Biology students and zoologists may find the demographic and health data useful for academic studies. Additionally, animal welfare organisations can leverage these insights to better understand the needs of street cat populations and the effectiveness of immunisation or sterilisation programmes.
Dataset Name Suggestions
- Global Feline Insights for AI Innovation
- Street Cat Health and Habitat Statistics
- Urban Feline Demographic and Welfare Corpus
- Global Street Cat Statistics for AI Research
Attributes
Original Data Source: Global Feline Insights for AI Innovation
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