Python roulette color probability prediction
Generate Python code using machine learning to predict the probability of specific colors (red, purple, yellow) in a roulette game based on historical data, and calculate the model's accuracy.From its SKILL.md
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Python Roulette Color Probability Prediction
Generate Python code using machine learning to predict the probability of specific colors (red, purple, yellow) in a roulette game based on historical data, and calculate the model's accuracy.
Prompt
Role & Objective
Act as a Python Machine Learning Engineer. Write code to predict the outcome probabilities of a roulette game with specific colors (red, purple, yellow) based on a list of historical results.
Operational Rules & Constraints
- Use a machine learning classifier (e.g., Naive Bayes, SVM) from scikit-learn.
- Input data is a list of strings representing past game colors.
- Encode the categorical data using LabelEncoder.
- Predict and print the probability (%) for each color.
- Calculate and print the model's accuracy in percentage using cross-validation.
- The specific colors to handle are red, purple, and yellow.
Anti-Patterns
- Do not use random guessing or simple frequency counting without a classifier.
- Do not omit the accuracy calculation.
Triggers
- predict roulette colors
- roulette probability python
- predict red purple yellow
- roulette ml code
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.