『仕事ではじめる機械学習』より

2_APIを介してバッチ処理で学習した予測結果を取得する.svg

2_APIを介してバッチ処理で学習した予測結果を取得する.uml

@startuml
skinparam monochrome true
skinparam backgroundColor #EEEEEE

actor アプリケーション as A
database DB as D
actor 予測APIサーバー as P
control 特徴抽出器 as F
collections 予測モデル as M
control 学習器 as L

group 予測
  A <-> D: - ユーザーID\n- 商品ID
  activate A
  A -> P: - ユーザーID\n- 商品ID
  activate P
  P -> F
  activate F
  F -> M: 特徴量
  deactivate F
  activate M
  M -> P
  deactivate M
  P -> A: 予測結果
  deactivate P
  deactivate A
end

group 学習バッチ
  D -> F: - ログ\n- ユーザー情報
  activate F
  F -> L: 特徴量
  deactivate F
  activate L
  L -> M: 学習結果
  deactivate L
end

@enduml

3_DBを介してバッチ処理で学習した予測結果を取得する.svg

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@startuml
skinparam monochrome true
skinparam backgroundColor #EEEEEE

actor アプリケーション as A
database DB as D
actor 予測APIサーバー as P
control 特徴抽出器 as F
collections 予測モデル as M
control 学習器 as L

group 予測参照
  A <-> D
end

group 予測バッチ
  D -> F: - ログ\n- ユーザー情報
  activate D
  activate F
  F -> M: 特徴量
  deactivate F
  activate M
  M -> D: 予測結果
  deactivate M
  deactivate D
end

group 学習バッチ
  D -> F: - ログ\n- ユーザー情報
  activate F
  F -> L: 特徴量
  deactivate F
  activate L
  L -> M: 学習結果
  deactivate L
end
@enduml

PlantUML version 1.2019.12(Sun Nov 03 10:24:54 UTC 2019)
(GPL source distribution)
Java Runtime: OpenJDK Runtime Environment
JVM: OpenJDK 64-Bit Server VM
Java Version: 1.8.0_232-heroku-b09
Operating System: Linux
Default Encoding: UTF-8
Language: en
Country: US
--></g></svg>

3_DBを介してバッチ処理で学習した予測結果を取得する.uml

@startuml
skinparam monochrome true
skinparam backgroundColor #EEEEEE

actor アプリケーション as A
database DB as D
actor 予測APIサーバー as P
control 特徴抽出器 as F
collections 予測モデル as M
control 学習器 as L

group 予測参照
  A <-> D
end

group 予測バッチ
  D -> F: - ログ\n- ユーザー情報
  activate D
  activate F
  F -> M: 特徴量
  deactivate F
  activate M
  M -> D: 予測結果
  deactivate M
  deactivate D
end

group 学習バッチ
  D -> F: - ログ\n- ユーザー情報
  activate F
  F -> L: 特徴量
  deactivate F
  activate L
  L -> M: 学習結果
  deactivate L
end

@enduml