Tabular Classification

the below parameters are for various tabular classification attack types to know more about the different attack input parameters see tabular classification docid\ mvtlctnkashpx9mzjvb62 the values presented below are examples taken from the model used in the reference implementation it is important to customize these values to achieve the best performance for your particular model extraction { "attack type" "blackbox", "categorical columns info" "job,marital,education,default,housing,loan,contact,poutcome", "defense bestonly" "no", "encryption strategy" "0", "input dimensions" "100,18", "is category columns" "yes", "model api details" "na", "model framework" "scikit learn", "normalize data" "yes", "number of attack queries" "10000", "number of classes" "2", "use model api" "no", "vulnerability threshold" "0 00" } evasion { "categorical columns info" "job,marital,education,default,housing,loan,contact,poutcome", "defense bestonly" "no", "encryption strategy" "1", "input dimensions" "41188,18", "is category columns" "yes", "model api details" "na", "model framework" "scikit learn", "normalize data" "yes", "number of classes" "2", "use model api" "no" } note in the response, copy job id this value is required to trigger the get apis see \<get> job metadata docid\ s mz7r0hnzicdqy6q 6hq the "job id" is used to retrieve model analysis metadata and check the processing status of the request it is also used for generating reports for the analyzed model copy the dashboard link from the response and open it in a new tab this allows users to monitor the job progress and download reports for using nodejs sample code, install npm package request given ample code for python is tested for python version 3 7 given sample code for nodejs and javascript is tested for node v20lts