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