Struct Explanation

#[non_exhaustive]
pub struct Explanation {
    pub attributions: Vec<Attribution>,
    pub neighbors: Vec<Neighbor>,
    /* private fields */
}

Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

attributions: Vec<Attribution>

Output only. Feature attributions grouped by predicted outputs.

For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining.

By default, we provide Shapley values for the predicted class. However, you can configure the explanation request to generate Shapley values for any other classes too. For example, if a model predicts a probability of 0.4 for approving a loan application, the model’s decision is to reject the application since p(reject) = 0.6 > p(approve) = 0.4, and the default Shapley values would be computed for rejection decision and not approval, even though the latter might be the positive class.

If users set ExplanationParameters.top_k, the attributions are sorted by instance_output_value in descending order. If ExplanationParameters.output_indices is specified, the attributions are stored by Attribution.output_index in the same order as they appear in the output_indices.

neighbors: Vec<Neighbor>

Output only. List of the nearest neighbors for example-based explanations.

For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated.

Implementations

impl Explanation

pub fn new() -> Self

pub fn set_attributions<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<Attribution>,

Sets the value of attributions.

pub fn set_neighbors<T, V>(self, v: T) -> Self

where T: IntoIterator<Item = V>, V: Into<Neighbor>,

Sets the value of neighbors.

Trait Implementations

impl Clone for Explanation

fn clone(&self) -> Explanation

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Explanation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Explanation

fn default() -> Explanation

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Explanation

where Explanation: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Message for Explanation

fn typename() -> &'static str

The typename of this message.

impl PartialEq for Explanation

fn eq(&self, other: &Explanation) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for Explanation

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for Explanation