Agroecological zoning of Nicaragua through multiple factor analysis and cluster analysis
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains the final product of an agroecological zone classification for Nicaragua. The classification was created using data layers from worldclim, soilgrid and INETER (Instituto Nicaragüense de Estudios Territoriales). The unsupervised method used was k-means and its inputs were variables obtained from a dimensionality reduction achieved through Multiple Factor Analysis. Finally, 17 clusters were pointed out, by a statistical metric and expert knowledge, as the best number of groups to describe the agroecological conditions for the country' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Agriculture","Agroecological zones","Digital Inclusion","Latin America and the Caribbean","Multifunctional Landscapes","Soil","Weather"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset contains the final product of an agroecological zone classification for Nicaragua. The classification was created using data layers from worldclim, soilgrid and INETER (Instituto Nicaragüense de Estudios Territoriales). The unsupervised method used was k-means and its inputs were variables obtained from a dimensionality reduction achieved through Multiple Factor Analysis. Finally, 17 clusters were pointed out, by a statistical metric and expert knowledge, as the best number of groups to describe the agroecological conditions for the country' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset contains the final product of an agroecological zone classification for Nicaragua. The classification was created using data layers from worldclim, soilgrid and INETER (Instituto Nicaragüense de Estudios Territoriales). The unsupervised method used was k-means and its inputs were variables obtained from a dimensionality reduction achieved through Multiple Factor Analysis. Finally, 17 clusters were pointed out, by a statistical metric and expert knowledge, as the best number of groups to describe the agroecological conditions for the country
Agriculture; Agroecological zones; Digital Inclusion; Latin America and the Caribbean; Multifunctional Landscapes; Soil; Weather