Get training request for a model
We trained “sales_model” previously, to view the training request that we sent, we can all this API. As you will see, ML engine adds some more data points to the request for help
Method : GET
URI : /ml/<schema-name>/<model_name>/request
Example
curl -X GET http://192.168.1.105:18080/ml/website/sales_model/request
Response
{
"schema-name":"website",
"training_details":{
"training_source":"visitor_upload.txt",
"file_size_mb":1,
"target_idx":5,
"input_format":"JSON",
"is_src_global":0,
"train_speed":3,
"bucket_name":"ml_bucket_info",
"training_source_type":1,
"expected_format":"SVM"
},
"algo_type":"SVM",
"tune_params":1,
"attr_list":[
{
"position":0,
"name":"vid"
},
{
"position":1,
"name":"prod"
},
{
"position":2,
"name":"pgid"
},
{
"position":3,
"name":"catid"
},
{
"name":"items",
"position":4
},
{
"name":"price",
"position":5
}
],
"scale":1,
"attr_type":3,
"algo_param":{
"probability":0,
"svm_type":3,
"eps_svr":0.1,
"kernel_type":0,
"shrinking":0,
"cost":100,
"termination_criteria":0.001
},
"model_name":"sales_model",
"train_start_ts":1648550728425224,
"train_end_ts":1648550728434816,
"train_req_state":25,
"tuned_algo_params":{
"C":0.0625,
"g":4,
"cache_size":100,
"coef0":0,
"degree":3,
"eps":0.001,
"kernel_type":0,
"nr_weight":0,
"nu":0.5,
"p":0.1,
"prob":0,
"shrinking":0,
"svm_type":3,
"train_perf":704
},
"train_log":{
"log":[
"1648550728424954 : received train request",
"verification done",
"retrieved the training file [ sales_model__website__visitor_upload.txt ] from BRS",
"file reformat done",
"scaling and tuning the model params, by training many different models",
"scaling and tuning done, selected params = 0.062500, 4.000000, 704.514490",
"starting training for model [ sales_model__website ]",
"1648550728434808 : training successful!"
],
"schema-name":"website",
"model_name":"sales_model",
"algo_type":"SVM",
"train_start_ts":1648550728425224,
"train_end_ts":1648550728434809,
"errorcode":0
}
}