Print Summary Statistics for Prototype Computation Objects

Displays a formatted summary of prototype-based classification results, showing both marginal and conditional probability distributions for categories and features. This method provides a comprehensive overview of how the prototype model distributes probability mass across categories and features.

Usage

# S3 method for class 'summary.prototypeComputation'
print(x, ...)

Arguments

x

A summary.prototypeComputation object created by summary.prototypeComputation.

...

Additional arguments passed to print methods (currently unused).

Value

Invisibly returns the input object x unchanged. The function is called primarily for its side effect of printing formatted output.

Details

The printed output is organized into two main sections:

Categories Section:

• Marginals: Overall probability of assignment to each category across all observations, computed as colMeans(object$probabilities)

• Conditionals: Two sub-lists showing P(C|X) - the probability of each category given feature values:

  • Xk=0: Category probabilities when each feature equals 0

  • Xk=1: Category probabilities when each feature equals 1

Features Section:

• Marginals: Overall probability that each feature equals 1 across all observations, computed as colMeans(object$data)

• Conditionals: The probability that each feature equals 1 given membership in each category, P(X|C).

All probability values are rounded to 3 decimal places for readability.