| id | a417112a-edd7-4ed8-905b-e0f971ce27b9 |
| name | Python Roulette Color Probability Prediction |
| description | 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. |
| version | 0.1.0 |
| tags | ["python","machine learning","roulette","prediction","probability"] |
| triggers | ["predict roulette colors","roulette probability python","predict red purple yellow","roulette ml code"] |
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
