Discovery Engine v1beta API - Class QualityMetrics (1.0.0-beta17)

public sealed class QualityMetrics : IMessage<QualityMetrics>, IEquatable<QualityMetrics>, IDeepCloneable<QualityMetrics>, IBufferMessage, IMessage

Reference documentation and code samples for the Discovery Engine v1beta API class QualityMetrics.

Describes the metrics produced by the evaluation.

Inheritance

object > QualityMetrics

Implements

IMessage QualityMetrics, IEquatable QualityMetrics, IDeepCloneable QualityMetrics, IBufferMessage, IMessage

Inherited Members

object.GetHashCode()

object.GetType()

object.ToString()

Namespace

Google.Cloud.DiscoveryEngine.V1Beta

Assembly

Google.Cloud.DiscoveryEngine.V1Beta.dll

Constructors

QualityMetrics()

public QualityMetrics()

QualityMetrics(QualityMetrics)

public QualityMetrics(QualityMetrics other)

Parameter
Name	Description
`other`	`QualityMetrics`

Properties

DocNdcg

public QualityMetrics.Types.TopkMetrics DocNdcg { get; set; }

Normalized discounted cumulative gain (NDCG) per document, at various top-k cutoff levels.

NDCG measures the ranking quality, giving higher relevance to top results.

Example (top-3): Suppose [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery] with three retrieved documents (D1, D2, D3) and binary relevance judgements (1 for relevant, 0 for not relevant):

Retrieved: [D3 (0), D1 (1), D2 (1)] Ideal: [D1 (1), D2 (1), D3 (0)]

Calculate NDCG@3 for each [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery]:

DCG@3: 0/log2(1+1) + 1/log2(2+1) + 1/log2(3+1) = 1.13
Ideal DCG@3: 1/log2(1+1) + 1/log2(2+1) + 0/log2(3+1) = 1.63
NDCG@3: 1.13/1.63 = 0.693

Property Value
Type	Description
`QualityMetricsTypesTopkMetrics`

DocPrecision

public QualityMetrics.Types.TopkMetrics DocPrecision { get; set; }

Precision per document, at various top-k cutoff levels.

Precision is the fraction of retrieved documents that are relevant.

Example (top-5):

For a single [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery], If 4 out of 5 retrieved documents in the top-5 are relevant, precision@5 = 4/5 = 0.8

Property Value
Type	Description
`QualityMetricsTypesTopkMetrics`

DocRecall

public QualityMetrics.Types.TopkMetrics DocRecall { get; set; }

Recall per document, at various top-k cutoff levels.

Recall is the fraction of relevant documents retrieved out of all relevant documents.

Example (top-5):

For a single [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery], If 3 out of 5 relevant documents are retrieved in the top-5, recall@5 = 3/5 = 0.6

Property Value
Type	Description
`QualityMetricsTypesTopkMetrics`

PageNdcg

public QualityMetrics.Types.TopkMetrics PageNdcg { get; set; }

Normalized discounted cumulative gain (NDCG) per page, at various top-k cutoff levels.

NDCG measures the ranking quality, giving higher relevance to top results.

Example (top-3): Suppose [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery] with three retrieved pages (P1, P2, P3) and binary relevance judgements (1 for relevant, 0 for not relevant):

Retrieved: [P3 (0), P1 (1), P2 (1)] Ideal: [P1 (1), P2 (1), P3 (0)]

Calculate NDCG@3 for [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery]:

DCG@3: 0/log2(1+1) + 1/log2(2+1) + 1/log2(3+1) = 1.13
Ideal DCG@3: 1/log2(1+1) + 1/log2(2+1) + 0/log2(3+1) = 1.63
NDCG@3: 1.13/1.63 = 0.693

Property Value
Type	Description
`QualityMetricsTypesTopkMetrics`

PageRecall

public QualityMetrics.Types.TopkMetrics PageRecall { get; set; }

Recall per page, at various top-k cutoff levels.

Recall is the fraction of relevant pages retrieved out of all relevant pages.

Example (top-5):

For a single [SampleQuery][google.cloud.discoveryengine.v1beta.SampleQuery], if 3 out of 5 relevant pages are retrieved in the top-5, recall@5 = 3/5 = 0.6

Property Value
Type	Description
`QualityMetricsTypesTopkMetrics`