Probabilistic#

Estimators that implement the Probabilistic interface have proba() and probaSample() methods that return an array of joint probability estimates for every possible class or cluster number. Probabilities are useful for ascertaining the degree to which the estimator is certain about a particular outcome. A value of 1 indicates that the estimator is 100% certain about a particular class or cluster number. Conversely, a value of 0 means that the estimator is 100% certain that it's not that class or cluster number. When the probabilities are considered together they are called a joint distribution and always sum to 1.

Predict Probabilities#

Return the joint probability estimates from a dataset:

public proba(Dataset $dataset) : array

Example

$probabilities = $estimator->proba($dataset);  

var_dump($probabilities);
array(2) {
    [0] => array(2) {
        ['monster'] => 0.975,
        ['not monster'] => 0.025,
    }
    [1] => array(2) {
        ['monster'] => 0.2,
        ['not monster'] => 0.8,
    }
    [2] => array(2) {
        ['monster'] => 0.6,
        ['not monster'] => 0.4,
    }
}

Probabilities of a Single Sample#

Predict the probabilities of a single sample and return the joint distribution:

public probaSample(array $sample) : array

Example

$probabilities = $estimator->probaSample(['mean', 'furry', 'loner', -0.25]);

var_dump($probabilities);
array(2) {
    ['monster'] => 0.6,
    ['not monster'] => 0.4,
}