Reference documentation and code samples for the Google Cloud Dialogflow V2 Client class ConversationModelEvaluation.
Represents evaluation result of a conversation model.
Generated from protobuf message google.cloud.dialogflow.v2.ConversationModelEvaluation
Namespace
Google \ Cloud \ Dialogflow \ V2Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ name
string
The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model ID>/evaluations/<Evaluation ID>
↳ display_name
string
Optional. The display name of the model evaluation. At most 64 bytes long.
↳ evaluation_config
↳ create_time
↳ smart_reply_metrics
Google\Cloud\Dialogflow\V2\SmartReplyMetrics
Output only. Only available when model is for smart reply.
↳ raw_human_eval_template_csv
string
Output only. Human eval template in csv format. It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.
getName
The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model
ID>/evaluations/<Evaluation ID>
string
setName
The resource name of the evaluation. Format: projects/<Project ID>/conversationModels/<Conversation Model
ID>/evaluations/<Evaluation ID>
var
string
$this
getDisplayName
Optional. The display name of the model evaluation. At most 64 bytes long.
string
setDisplayName
Optional. The display name of the model evaluation. At most 64 bytes long.
var
string
$this
getEvaluationConfig
Optional. The configuration of the evaluation task.
hasEvaluationConfig
clearEvaluationConfig
setEvaluationConfig
Optional. The configuration of the evaluation task.
$this
getCreateTime
Output only. Creation time of this model.
hasCreateTime
clearCreateTime
setCreateTime
Output only. Creation time of this model.
$this
getSmartReplyMetrics
Output only. Only available when model is for smart reply.
hasSmartReplyMetrics
setSmartReplyMetrics
Output only. Only available when model is for smart reply.
$this
getRawHumanEvalTemplateCsv
Output only. Human eval template in csv format.
It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.
string
setRawHumanEvalTemplateCsv
Output only. Human eval template in csv format.
It tooks real-world conversations provided through input dataset, generates example suggestions for customer to verify quality of the model. For Smart Reply, the generated csv file contains columns of Context, (Suggestions,Q1,Q2)*3, Actual reply. Context contains at most 10 latest messages in the conversation prior to the current suggestion. Q1: "Would you send it as the next message of agent?" Evaluated based on whether the suggest is appropriate to be sent by agent in current context. Q2: "Does the suggestion move the conversation closer to resolution?" Evaluated based on whether the suggestion provide solutions, or answers customer's question or collect information from customer to resolve the customer's issue. Actual reply column contains the actual agent reply sent in the context.
var
string
$this
getMetrics
string
