/
cml.json
143 lines (142 loc) · 3.14 KB
/
cml.json
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{
"name":"FinTech",
"description":"Transforms FinTech mostly catagorical data to useable format",
"version":"0.0.1",
"createdDate":"20190913",
"model":{
"framework":"Tensorflow",
"tags":"serve",
"signatureDefs":"def_signature"
},
"input": [
{
"type": "array",
"label":"dataIn"
}
],
"structure": [
{
"operation":"concatMap",
"input":{
"data":"$dataIn"
},
"output":"datatemp"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['Age']",
"value":100,
"minvalue":18
},
"output":"datatemp['Age']"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['Amount']",
"value":500
},
"output":"datatemp['Amount']"
},
{
"operation":"replaceValue",
"input":
{
"data":"$datatemp",
"replaceMap":{"f":1,"m":0}
},
"params":{"col":["gender"]},
"output":"datatemp"
},
{
"operation":"oneHotEncoding",
"input":{"data":"$datatemp"},
"params":{
"col": ["bank","cardType","entry_type","transaction"],
"separateOut":false
},
"output":"datatemp"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['v1']",
"value":5,
"minvalue":-5
},
"output":"datatemp['v1']"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['v2']",
"value":5,
"minvalue":-5
},
"output":"datatemp['v2']"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['v3']",
"value":5,
"minvalue":-5
},
"output":"datatemp['v3']"
},
{
"operation":"normalize",
"input":{
"data":"$datatemp['v4']",
"value":5,
"minvalue":-5
},
"output":"datatemp['v4']"
},
{
"operation":"multPairWise",
"input":{
"matrix0":"$datatemp['v4']",
"matrix1":"$datatemp['v3']"
},
"output":"datatemp['v3*v4']"
},
{
"operation":"multPairWise",
"input":{
"matrix0":"$datatemp['v3*v4']",
"matrix1":"$datatemp['Visa']"
},
"output":"datatemp['v3*v4*Visa']"
},
{
"operation":"multPairWise",
"input":{
"matrix0":"$datatemp['v2']",
"matrix1":"$datatemp['v1']"
},
"output":"datatemp['v1*v2']"
},
{
"operation":"multPairWise",
"input":{
"matrix0":"$datatemp['v1*v2']",
"matrix1":"$datatemp['Master']"
},
"output":"datatemp['v1*v2*Master']"
},
{
"operation":"map2table",
"input": {
"map":"$datatemp",
"colOrder": ["ATM","Age","AmEx","Amount","Bank0","Bank1","Bank10","Bank2","Bank3","Bank4","Bank5","Bank6","Bank7","Bank8","Bank9","INTERNET","Master","Master_Debit","POS","Visa","Visa_Debit","chip","gender","magnetic","v1","v2","v3","v4","v3*v4*Master","v3*v4*Visa","fraud"]
},
"output":"datatab"
}
],
"output": {
"type": "object",
"data":{"output":"$datatemp"}
}
}