// DTOs
variable = {
"id":int,
"name":string,
"typeId":int[0|1],
"values":[double]
}
dataset = {
"datasetname":string,
"variables":[variable],
"normalizationMethodId":int
}
dataType = {
"id":int[0|1], // numerical or categorical
"name":string
}
normalizationMethod = {
"id":int,
"name":string,
"typeId":int[0|1]
}
clusteringAlgorithm = {
"id":int,
"name":string
}
clusteringDescription = {
"graph":image,
"description":string
}send .csv dataset to server
download exported .csv dataset
return overview of analyzed dataset: data with only n values for each variable
update dataset overview
returns graph
return list of available normalization methods: [normalizationMethods]
return list of available dataTypes: [dataType]
upload list of chosen variables ids along with chosen clustering method id
return image with string describing it
return list of cluesting methods
return graph which shows importance of each feature after PCA
return data after perform PCA but it doesn't change original dataset
perform PCA on original data and change it