Table 1.
Overview of primary education in Shanghai, China.
Table 2.
Classification and types of school sports facilities (SSFs).
Fig 1.
Overview of data processing and modeling pipeline on the assessment of PSSFC.
Fig 2.
The comparison of the fuzzy partition coefficient (FPC) for the selecting centers of FCM.
Fig 3.
The degree of membership of PSSFC for each primary school clustered by FCM (c = 3).
(1) All sampled schools in the initial order and random sort. (2) Sorted by the DM for each school belong to every cluster.
Fig 4.
Embedding of clustered PSSFC into two dimensions via t-SNE.
Table 3.
Descriptive statistics of classified PSSFC by using machine learning (n = 845).
Table 4.
Relationships between school location and school category and PSSFC.
Table 5.
Numeric statistics on 3 types of PSSFC clustered by using machine learning.
Fig 5.
Geographical distribution of PSSFC with three categories in Shanghai.
(A) The geographical distribution panorama of PSSFC in Shanghai. (B) The distribution of Type-1 PSSFC in Shanghai. (C) The distribution of Type-2 PSSFC in Shanghai. (D) The distribution of Type-3 PSSFC in Shanghai.
Fig 6.
Geographical distribution of f PSSFC with three categories in urban districts in Shanghai by zoomed in to the scope of the urban area (distance ≤15 kilometers to the Shanghai Municipal Peoples’ Government).