lib/elasticsearch-serverless/api/machine_learning/evaluate_data_frame.rb

# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. licenses this file to you under
# the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#
# Auto generated from commit f284cc16f4d4b4289bc679aa1529bb504190fe80
# @see https://github.com/elastic/elasticsearch-specification
#
module ElasticsearchServerless
  module API
    module MachineLearning
      module Actions
        # Evaluate data frame analytics.
        # The API packages together commonly used evaluation metrics for various types
        # of machine learning features. This has been designed for use on indexes
        # created by data frame analytics. Evaluation requires both a ground truth
        # field and an analytics result field to be present.
        #
        # @option arguments [Hash] :headers Custom HTTP headers
        # @option arguments [Hash] :body request body
        #
        # @see https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-ml-evaluate-data-frame
        #
        def evaluate_data_frame(arguments = {})
          request_opts = { endpoint: arguments[:endpoint] || 'ml.evaluate_data_frame' }

          raise ArgumentError, "Required argument 'body' missing" unless arguments[:body]

          arguments = arguments.clone
          headers = arguments.delete(:headers) || {}

          body = arguments.delete(:body)

          method = ElasticsearchServerless::API::HTTP_POST
          path   = '_ml/data_frame/_evaluate'
          params = {}

          ElasticsearchServerless::API::Response.new(
            perform_request(method, path, params, body, headers, request_opts)
          )
        end
      end
    end
  end
end