クラスターインサイト¶
クラスターインサイトの可視化により、データセット内の各クラスターを理解し、名前を付けることができます。 クラスタリングによって、データの潜在的な特徴量を捉えたり、実用的なインサイトを迅速に把握して伝達したり、さらにモデリングするためにデータ内のセグメントを識別したりすることができます。
備考
クラスターインサイトで計算される特徴量の最大数は100です。特徴量は、モデルのトレーニングに使用された特徴量から、特徴量のインパクト（高～低）に基づいて選択されます。 残りの特徴量（モデルのトレーニングに使用されていないもの）はアルファベット順にソートされます。
To analyze the clusters in your data, after building a clustering experiment, select a model from the Leaderboard and open the Cluster Insights visualization.
次の表は、クラスターインサイトの可視化について説明しています。
| 要素 | 説明 | |
|---|---|---|
| 1 | Visualization controls | Provides tools for working with the display. |
| 2 | Clusters and features | Provides cluster and feature details, including visualizing cluster breakdown by feature and listing features, sorted by feature importance. The Informative Feature list displays by default; use the Feature list dropdown in the controls to change the display. |
Visualization controls¶
Use the controls in the top bar to work with the display.
クラスターを選択¶
Use Select clusters to add or remove clusters from the visualization view (not from the experiment). The visualization supports a maximum of five clusters per screen (use the arrow on the far right )
Click + Add cluster to display additional clusters; delete a cluster from the display with the trash can . To reorder clusters, click a cluster in a position and re-assign a new cluster to that position.
クラスターの名前を変更する¶
You can rename clusters after you gain an understanding of what they represent. クラスター名は他のインサイトと予測に反映され、クラスターをさらに分析できます。 Click Rename clusters, edit cluster names, and click Finish editing when done.
Change or create feature lists¶
By default, DataRobot builds clustering models using the Informative Features list. Select another feature list, either automatically generated or custom, to explore a different subset of features. Changing the list does not impact the model, only the display; however, analyzing the features not used to generate the clusters can still be useful to answer questions like "How does income distribute among my clusters, even if I'm not using it for clustering?"
See the custom feature list reference for information on creating new lists.
検索¶
Use Search to show an individual feature's placement in each cluster.
CSVのダウンロード¶
Click Download CSV to download the cluster insights. CSVには、可視化されたクラスターインサイトに表示される情報と、より詳細な特徴量データが含まれます。
View more features¶
Features display, for each displayed cluster, in order of Feature Impact, most important to least by default. Four features display by default; click the number to adjust the number of features displayed per page. 特徴量のページを移動するには、クラスターの上の右矢印をクリックします。
Clusters and features¶
Clusters are comprised of groups of similar features that form natural segments. The Clustering Insights visualization helps to understand how those groups were formed. See the reference documentation for details on investigating cluster features.
Clusters display in columns, showing the features in the cluster and the feature impact score and values for each feature. The visualization helps to evaluate the distribution of features across clusters. Cluster sizes are shown as percentages above the cluster name. The All data cluster contains 100% as a baseline comparison.
- Click the arrow to the right of the cluster names to scroll through cluster.
- Click the Impact column name to reverse the order.
Hover on a feature within a cluster to see details for the top four features.
Expand a row to see additional features or statistics, depending on feature type, within a cluster.
数値特徴量の場合：
For categorical features, see a histogram showing the top four features and all others bucketed into Other:
To drill into all categories, click the gear :fontawesome-gear: next to the feature name and select High cardinality. Hover on a value how many records in the selected cluster contain that value.
