Trait InferableReasoning

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pub trait InferableReasoning<T>where
    T: Inferable,{
Show 16 methods    // Required methods
    fn len(&self) -> usize;
    fn is_empty(&self) -> bool;
    fn get_all_items(&self) -> Vec<&T>;

    // Provided methods
    fn get_all_inferable(&self) -> Vec<&T> { ... }
    fn get_all_inverse_inferable(&self) -> Vec<&T> { ... }
    fn get_all_non_inferable(&self) -> Vec<&T> { ... }
    fn all_inferable(&self) -> bool { ... }
    fn all_inverse_inferable(&self) -> bool { ... }
    fn all_non_inferable(&self) -> bool { ... }
    fn conjoint_delta(&self) -> NumericalValue { ... }
    fn number_inferable(&self) -> NumericalValue { ... }
    fn number_inverse_inferable(&self) -> NumericalValue { ... }
    fn number_non_inferable(&self) -> NumericalValue { ... }
    fn percent_inferable(&self) -> NumericalValue { ... }
    fn percent_inverse_inferable(&self) -> NumericalValue { ... }
    fn percent_non_inferable(&self) -> NumericalValue { ... }
}

Expand description

Trait providing reasoning methods for collections of Inferable items.

Provides methods for:

Filtering inferable/non-inferable items
Checking if all items are inferable
Calculating inferability metrics
- conjoint_delta
- Counts
- Percentages

Requires Inferable items that implement:

is_inferable()
is_inverse_inferable()

Provides default implementations using those methods.

Required Methods§

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fn len(&self) -> usize

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fn is_empty(&self) -> bool

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fn get_all_items(&self) -> Vec<&T>

Provided Methods§

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fn get_all_inferable(&self) -> Vec<&T>

Returns a vector containing all inferable items.

Filters the full set of items based on is_inferable().

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fn get_all_inverse_inferable(&self) -> Vec<&T>

Returns a vector containing all inverse inferable items.

Filters the full set of items based on is_inverse_inferable().

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fn get_all_non_inferable(&self) -> Vec<&T>

Returns a vector containing all non-inferable items.

An item is non-inferable if it is both inferable and inverse inferable, which makes it undecidable.

Filters the full set of items based on:

is_inferable()
is_inverse_inferable()

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fn all_inferable(&self) -> bool

Checks if all items in the collection are inferable.

Iterates through all items and checks is_inferable() on each.

Returns:

true if all items are inferable
false if any item is not inferable

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fn all_inverse_inferable(&self) -> bool

Checks if all items in the collection are inverse inferable.

Iterates through all items and checks is_inverse_inferable() on each.

Returns:

true if all items are inverse inferable
false if any item is not inverse inferable

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fn all_non_inferable(&self) -> bool

Checks if all items in the collection are non-inferable.

An item is non-inferable if it is both inferable and inverse inferable.

Iterates through all items and checks:

is_inferable()
is_inverse_inferable()

Returns:

true if any item is both inferable and inverse inferable
false if no items meet that criteria

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fn conjoint_delta(&self) -> NumericalValue

Estimates the ConJointDelta for this collection.

The conjoint delta represents the combined effect of unobserved factors and is used to determine the strength of the joint causal relationship.

It is calculated as the difference (delta) between the combined (joint) observation (conjecture) and a theoretical 100% if the conjecture were to explain all observations, hence the name ConJointDelta:

1.0 - (sum of observations / total items)

Where:

sum of observations = total items - non-inferable items
total items = length of the collection
non-inferable items = count of non-inferable items

Finally, the absolute value is taken.

The resulting value is interpreted as following:

Higher: THe higher the conjoint delta, the more unobserved factors are present and observed factors are not explaining the observation. Therefore, the joint causal relationship is weaker and doesn’t explain much of the observation.

Lower: The lower the conjoint delta, the more the observed factors explain the observation. Therefore, the joint causal relationship is stronger as it explains more of the observation.

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