Enum google_api_proto::google::cloud::bigquery::v2::model::hparam_tuning_enums::HparamTuningObjective

#[repr(i32)]
pub enum HparamTuningObjective {
    Unspecified = 0,
    MeanAbsoluteError = 1,
    MeanSquaredError = 2,
    MeanSquaredLogError = 3,
    MedianAbsoluteError = 4,
    RSquared = 5,
    ExplainedVariance = 6,
    Precision = 7,
    Recall = 8,
    Accuracy = 9,
    F1Score = 10,
    LogLoss = 11,
    RocAuc = 12,
    DaviesBouldinIndex = 13,
    MeanAveragePrecision = 14,
    NormalizedDiscountedCumulativeGain = 15,
    AverageRank = 16,
}

Available evaluation metrics used as hyperparameter tuning objectives.

Variants

Unspecified = 0

Unspecified evaluation metric.

MeanAbsoluteError = 1

Mean absolute error. mean_absolute_error = AVG(ABS(label - predicted))

MeanSquaredError = 2

Mean squared error. mean_squared_error = AVG(POW(label - predicted, 2))

MeanSquaredLogError = 3

Mean squared log error. mean_squared_log_error = AVG(POW(LN(1 + label) - LN(1 + predicted), 2))

MedianAbsoluteError = 4

Mean absolute error. median_absolute_error = APPROX_QUANTILES(absolute_error, 2)[OFFSET(1)]

RSquared = 5

R^2 score. This corresponds to r2_score in ML.EVALUATE. r_squared = 1 - SUM(squared_error)/(COUNT(label)*VAR_POP(label))

ExplainedVariance = 6

Explained variance. explained_variance = 1 - VAR_POP(label_error)/VAR_POP(label)

Precision = 7

Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.

Recall = 8

Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.

Accuracy = 9

Accuracy is the fraction of predictions given the correct label. For multiclass this is a globally micro-averaged metric.

F1Score = 10

The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.

LogLoss = 11

Logorithmic Loss. For multiclass this is a macro-averaged metric.

RocAuc = 12

Area Under an ROC Curve. For multiclass this is a macro-averaged metric.

DaviesBouldinIndex = 13

Davies-Bouldin Index.

MeanAveragePrecision = 14

Mean Average Precision.

NormalizedDiscountedCumulativeGain = 15

Normalized Discounted Cumulative Gain.

AverageRank = 16

Average Rank.

Implementations

impl HparamTuningObjective

pub fn is_valid(value: i32) -> bool

Returns true if value is a variant of HparamTuningObjective.

pub fn from_i32(value: i32) -> Option<HparamTuningObjective>

👎Deprecated: Use the TryFrom<i32> implementation instead

Converts an i32 to a HparamTuningObjective, or None if value is not a valid variant.

impl HparamTuningObjective

pub fn as_str_name(&self) -> &'static str

String value of the enum field names used in the ProtoBuf definition.

The values are not transformed in any way and thus are considered stable (if the ProtoBuf definition does not change) and safe for programmatic use.

pub fn from_str_name(value: &str) -> Option<Self>

Creates an enum from field names used in the ProtoBuf definition.

Trait Implementations

impl Clone for HparamTuningObjective

fn clone(&self) -> HparamTuningObjective

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for HparamTuningObjective

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

Formats the value using the given formatter.

impl Default for HparamTuningObjective

fn default() -> HparamTuningObjective

Returns the “default value” for a type.

impl From<HparamTuningObjective> for i32

fn from(value: HparamTuningObjective) -> i32

Converts to this type from the input type.

impl Hash for HparamTuningObjective

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl Ord for HparamTuningObjective

fn cmp(&self, other: &HparamTuningObjective) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized + PartialOrd,

Restrict a value to a certain interval.

impl PartialEq for HparamTuningObjective

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl PartialOrd for HparamTuningObjective

fn partial_cmp(&self, other: &HparamTuningObjective) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

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

This method tests less than (for self and other) and is used by the < operator.

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

This method tests less than or equal to (for self and other) and is used by the <= operator.

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

This method tests greater than (for self and other) and is used by the > operator.

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

This method tests greater than or equal to (for self and other) and is used by the >= operator.

impl TryFrom<i32> for HparamTuningObjective

type Error = UnknownEnumValue

The type returned in the event of a conversion error.

fn try_from(value: i32) -> Result<HparamTuningObjective, UnknownEnumValue>

Performs the conversion.

impl Copy for HparamTuningObjective

impl Eq for HparamTuningObjective

impl StructuralPartialEq for HparamTuningObjective