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| author | Danijel Anđelković <adanijel99@gmail.com> | 2022-04-20 00:04:19 +0200 |
|---|---|---|
| committer | Danijel Anđelković <adanijel99@gmail.com> | 2022-04-20 00:04:19 +0200 |
| commit | b25af94d6df8854129e99f77638e4013a9c57086 (patch) | |
| tree | 46496e2d5630de85244e6814024e3f289c6c84e8 /backend/microservice/api | |
| parent | 092ea8c9a0a80857e2da47abc789d48d79af405a (diff) | |
Povezao metric view komponentu, chart, sa signalR tako da se iscrtavaju metrike modela kako se trenira. Ispravio neke bug-ove.
Diffstat (limited to 'backend/microservice/api')
| -rw-r--r-- | backend/microservice/api/newmlservice.py | 20 |
1 files changed, 16 insertions, 4 deletions
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index 9e09186f..6cbda69c 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -129,7 +129,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): ###NULL null_value_options = paramsExperiment["nullValues"] null_values_replacers = paramsExperiment["nullValuesReplacers"] - + if(null_value_options=='replace'): #print("replace null") # dict=null_values_replacers @@ -138,8 +138,13 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): col=replace['column'] opt=replace['option'] if(opt=='replace'): - replacevalue=replace['value'] - data[col]=data[col].fillna(replacevalue) + val = replace['value'] + if(data[col].dtype == 'int64'): + val = np.int64(val) + elif(data[col].dtype == 'float64'): + val = np.float64(val) + #elif(data[col].dtype == 'object'): + data[col]=data[col].fillna(val) elif(null_value_options=='delete_rows'): data=data.dropna() elif(null_value_options=='delete_columns'): @@ -167,7 +172,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): ''' - encodings=paramsExperiment["encoding"] + encodings=paramsExperiment["encodings"] datafront=dataset.copy() svekolone=datafront.columns kategorijskekolone=datafront.select_dtypes(include=['object']).columns @@ -232,6 +237,13 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback): #print(x_columns) x = data[x_columns].values y = data[output_column].values + print('-----------------dfghfhgfhfg-------------------------------') + print(x) + print('-----------------dfghfhgfhfg-------------------------------') + print(y) + print('-----------------dfghfhgfhfg-------------------------------') + print(output_column) + print('-----------------dfghfhgfhfg-------------------------------') # # Podela na test i trening skupove |