Data Structure ?
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Data Structure ?
*The above analysis is the result extracted and analyzed by the system, and the specific actual data shall prevail.
README.md
コンテキスト
タクシーの移動時間を予測するというタスクがある場合、都市の基礎となる道路網をより深く調べることは有益です。ネットワーク分析により、いくつかの基本的なネットワーク特性を考慮して、なぜ特定のタクシーの移動時間が他のものより長くなるのかを理解することができます。分析の例としては、最短経路を計算する、特定の道路がネットワークの堅牢性に与える影響を測定する、または交通流量に関してネットワークの重要ポイントとなる道路を見つけることが挙げられます。
内容
このデータセットには、GraphML形式のニューヨーク市の道路網の1つの大きなグラフと、分析の高速テスト用のマンハッタン地区のサブグラフが含まれています。
各グラフは、https://github.com/gboeing/osmnx という素晴らしいPythonパッケージを使用して作成されていますが、このパッケージはKaggleでは利用できません。グラフのノード属性はOSMから取得されており、他のどのノードに接続されているか、接続の長さはどれくらいか、制限速度はどれくらいかなどの情報が含まれています。
謝辞
https://github.com/gboeing/osmnx
インスピレーション
ニューヨークの道路網を探索し、ネットワーク分析についてより深い理解を得て、タクシー移動時間予測コンペティションに役立つ特徴量を作成しましょう！
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