Mendapatkan evaluasi model

Mendemonstrasikan pengambilan evaluasi model.

Contoh kode

Java

Untuk melakukan autentikasi ke AutoML Tables, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, baca Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import com.google.cloud.automl.v1beta1.AutoMlClient;
import com.google.cloud.automl.v1beta1.ModelEvaluation;
import com.google.cloud.automl.v1beta1.ModelEvaluationName;
import java.io.IOException;

class GetModelEvaluation {

  static void getModelEvaluation() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR_PROJECT_ID";
    String modelId = "YOUR_MODEL_ID";
    String modelEvaluationId = "YOUR_MODEL_EVALUATION_ID";
    getModelEvaluation(projectId, modelId, modelEvaluationId);
  }

  // Get a model evaluation
  static void getModelEvaluation(String projectId, String modelId, String modelEvaluationId)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
      // Get the full path of the model evaluation.
      ModelEvaluationName modelEvaluationFullId =
          ModelEvaluationName.of(projectId, "us-central1", modelId, modelEvaluationId);

      // Get complete detail of the model evaluation.
      ModelEvaluation modelEvaluation = client.getModelEvaluation(modelEvaluationFullId);

      System.out.format("Model Evaluation Name: %s%n", modelEvaluation.getName());
      System.out.format("Model Annotation Spec Id: %s", modelEvaluation.getAnnotationSpecId());
      System.out.println("Create Time:");
      System.out.format("\tseconds: %s%n", modelEvaluation.getCreateTime().getSeconds());
      System.out.format("\tnanos: %s", modelEvaluation.getCreateTime().getNanos() / 1e9);
      System.out.format(
          "Evalution Example Count: %d%n", modelEvaluation.getEvaluatedExampleCount());

      System.out.format(
          "Classification Model Evaluation Metrics: %s%n",
          modelEvaluation.getClassificationEvaluationMetrics());

      System.out.format(
          "Video Object Tracking Evaluation Metrics: %s%n",
          modelEvaluation.getVideoObjectTrackingEvaluationMetrics());
    }
  }
}

Python

Untuk melakukan autentikasi ke AutoML Tables, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, baca Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

# TODO(developer): Uncomment and set the following variables
# project_id = 'PROJECT_ID_HERE'
# compute_region = 'COMPUTE_REGION_HERE'
# model_id = 'MODEL_ID_HERE'
# model_evaluation_id = 'MODEL_EVALUATION_ID_HERE'

from google.cloud import automl_v1beta1 as automl

client = automl.TablesClient()

# Get the full path of the model evaluation.
model_path = client.auto_ml_client.model_path(project_id, compute_region, model_id)
model_evaluation_full_id = f"{model_path}/modelEvaluations/{model_evaluation_id}"

# Get complete detail of the model evaluation.
response = client.get_model_evaluation(
    model_evaluation_name=model_evaluation_full_id
)

print(response)

Langkah selanjutnya

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