Textile Dataset for Applying into Machine Learning Models

With the help of domain experts we created a data set containing a total of 1,600 fabrics divided into sixteen different categories, each containing 100 items of a particular type of textile. On average, each textile consists of 20,916 vertices, 5,229 hyperedges, 152 terminal nodes, 5,229 regular edges and 10,534 connected edges. The attached file is hypergraph representations which are extracted to k-neighbourhoods and then transferred to vector representations with normal frequence and TF-IDF. These vectors are applied into ML models.