{"templateId":"markdown","sharedDataIds":{"sidebar":"sidebar-@l10n/ja/sidebars.yaml"},"props":{"metadata":{"markdoc":{"tagList":[]},"type":"markdown"},"seo":{"title":"AutoML ノートブックソリューション","description":"Treasure AI AutoMLのノートブックソリューション。分類、回帰、予測、SHAP分析など、多様なMLソリューションを提供。ビジネスユース向けに対応。","siteUrl":"https://docs.treasure.ai","lang":"en-US","jsonLd":{"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://www.treasure.ai/","name":"Treasure AI","url":"https://www.treasure.ai/","logo":"https://www.treasure.ai/hubfs/assets/images/logos/primary-logo.svg"},{"@type":"WebSite","@id":"https://docs.treasure.ai/#website","name":"Treasure AI Documentation","url":"https://docs.treasure.ai/","inLanguage":["en","ja"],"publisher":{"@id":"https://www.treasure.ai/"}}]},"llmstxt":{"hide":false,"sections":[{"title":"Table of contents","includeFiles":["**/*"],"excludeFiles":[]}],"excludeFiles":[]}},"dynamicMarkdocComponents":[],"compilationErrors":[],"ast":{"$$mdtype":"Tag","name":"article","attributes":{},"children":[{"$$mdtype":"Tag","name":"Heading","attributes":{"level":1,"id":"automl-ノートブックソリューション","__idx":0},"children":["AutoML ノートブックソリューション"]},{"$$mdtype":"Tag","name":"p","attributes":{},"children":["Treasure AutoMLは複数のソリューションノートブックを提供しています:"," ",{"$$mdtype":"Tag","name":"img","attributes":{"src":"/assets/solution-package-tree.d1ed4d1f9969467e78b49eb82c7bf8bb830e4c66060576d2d023c489d71ac40f.3cb60505.png","alt":""},"children":[]}]},{"$$mdtype":"Tag","name":"p","attributes":{},"children":["基本ノートブックには、AutoGluonによる分類/回帰、時系列予測、EDA、SHAP説明、さらにサンプルMLデータセットを準備するためのノートブックが含まれています。現在のソリューション例: Next Best Actions、Multi-Touch Attribution、ネットワーク分析。"]},{"$$mdtype":"Tag","name":"Heading","attributes":{"level":2,"id":"ベースパッケージ","__idx":1},"children":["ベースパッケージ"]},{"$$mdtype":"Tag","name":"p","attributes":{},"children":["ベースパッケージには、AutoGluonを使用した基本的な分類/回帰ノートブックが含まれています。AutoGluonは多層スタッキングを使用して、多様なMLモデルを組み合わせます。詳細については、",{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"https://auto.gluon.ai/stable/index.html"},"children":["AutoGluonドキュメント"]},"を参照してください。"]},{"$$mdtype":"Tag","name":"p","attributes":{},"children":["また、クイックスタートのためにサンプルMLデータセットを準備するノートブックも含まれています。"]},{"$$mdtype":"Tag","name":"div","attributes":{"className":"md-table-wrapper"},"children":[{"$$mdtype":"Tag","name":"table","attributes":{"className":"md"},"children":[{"$$mdtype":"Tag","name":"thead","attributes":{},"children":[{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"th","attributes":{"data-label":"ベースパッケージ"},"children":[{"$$mdtype":"Tag","name":"strong","attributes":{},"children":["ベースパッケージ"]}]},{"$$mdtype":"Tag","name":"th","attributes":{"data-label":"説明"},"children":[{"$$mdtype":"Tag","name":"strong","attributes":{},"children":["説明"]}]}]}]},{"$$mdtype":"Tag","name":"tbody","attributes":{},"children":[{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/gluon-train"},"children":["Gluon Train"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["入力トレーニングテーブルでAutoGluonライブラリを使用してモデルをトレーニングします。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/gluon-predict"},"children":["Gluon Predict"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["Gluon Trainで作成されたモデルを使用して値を予測します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/ml-datasets"},"children":["ML Datasets"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["サンプルMLデータセットをTDデータテーブルとして読み込みます。"]}]}]}]}]},{"$$mdtype":"Tag","name":"Heading","attributes":{"level":2,"id":"ソリューションパッケージ","__idx":2},"children":["ソリューションパッケージ"]},{"$$mdtype":"Tag","name":"p","attributes":{},"children":["事前設定されたソリューションパッケージは、特定のビジネスユースケースに対応しています。"]},{"$$mdtype":"Tag","name":"div","attributes":{"className":"md-table-wrapper"},"children":[{"$$mdtype":"Tag","name":"table","attributes":{"className":"md"},"children":[{"$$mdtype":"Tag","name":"thead","attributes":{},"children":[{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"th","attributes":{"data-label":"ソリューションパッケージ"},"children":[{"$$mdtype":"Tag","name":"strong","attributes":{},"children":["ソリューションパッケージ"]}]},{"$$mdtype":"Tag","name":"th","attributes":{"data-label":"説明"},"children":[{"$$mdtype":"Tag","name":"strong","attributes":{},"children":["説明"]}]}]}]},{"$$mdtype":"Tag","name":"tbody","attributes":{},"children":[{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/next-best-action"},"children":["Next Best Action"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["過去の行動に基づいて、顧客価値を高める可能性が最も高いマーケティングアクションを予測します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/multi-touch-attribution"},"children":["Multi-touch Attribution (MTA)"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["KPI(コンバージョンなど)に向けたジャーニータッチポイントにクレジットを割り当てます。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/time-series-forecasting"},"children":["Time Series Forecasting"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["履歴データから潜在的な将来の値を予測し、戦略に情報を提供します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/exploratory-data-analysis"},"children":["Exploratory Data Analysis"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["データを探索し、モデリングの準備をするためのグラフィカル/統計的分析。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/shap-analysis"},"children":["SHAP Analysis"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["ローカル/グローバルなモデル説明可能性のためにShapley値を計算します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/network-analysis"},"children":["Network Analysis"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["Webアクセスパスのインサイトを得るためにSankeyダイアグラムとネットワークプロットを生成します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/rfm-analysis"},"children":["RFM Analysis"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["リーセンシー、頻度、金額価値(RFM)で顧客をセグメント化します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/clustering"},"children":["Clustering"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["特徴量の重要度とSHAP説明を含むクラスター(K-means)を作成します。"]}]},{"$$mdtype":"Tag","name":"tr","attributes":{},"children":[{"$$mdtype":"Tag","name":"td","attributes":{},"children":[{"$$mdtype":"Tag","name":"MarkdownLink","attributes":{"href":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions/cltv-prediction"},"children":["CLTV Prediction"]}]},{"$$mdtype":"Tag","name":"td","attributes":{},"children":["顧客生涯価値(CLTV)を推定します。"]}]}]}]}]}]},"headings":[{"value":"AutoML ノートブックソリューション","id":"automl-ノートブックソリューション","depth":1},{"value":"ベースパッケージ","id":"ベースパッケージ","depth":2},{"value":"ソリューションパッケージ","id":"ソリューションパッケージ","depth":2}],"frontmatter":{"seo":{"title":"AutoML ノートブックソリューション","description":"Treasure AI AutoMLのノートブックソリューション。分類、回帰、予測、SHAP分析など、多様なMLソリューションを提供。ビジネスユース向けに対応。"}},"lastModified":"2026-06-17T07:22:53.000Z","pagePropGetterError":{"message":"","name":""}},"slug":"/ja/products/customer-data-platform/machine-learning/automl/notebook-solutions","userData":{"isAuthenticated":false,"teams":["anonymous"]},"isPublic":true}