ML classification using with model for same data give other probabilities

ML classification using with model for same data give other probabilities
0

ml classification using with model for same data give other probabilities,
I developed small ML classification which use with python,
I created model with good precision and recall,
and then save it into pickle,
When I try test , I took one of the object from base data ,and run on pickle got other probabilities ,
If I created again the model and run with all base data getting all time the same values , but when use with his pickle got other results,
the code use with model look like this:

def text_to_features(doc, nlp_model):
    print(doc)
    try:
        features = (nlp_model).transform(doc)
        return True, features
    except:
        return False, ""
text_to_feature_success, ticket_features = text_to_features(df_case_specific, transformer)
def classifications_probabilities(features, classification_model):
    try:
        probabilities = (classification_model).predict_proba(features).tolist()[0]
        return True, probabilities
    except:
        return False, [] 
#Predict flow probabilities
probabilities_success, predicted_flow_prob_list = classifications_probabilities(ticket_features, model) 

Thanks,

thank you ,
I uploaded screen shot:

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I’ve edited your post for readability. When you enter a code block into a forum post, please precede it with a separate line of three backticks and follow it with a separate line of three backticks to make easier to read.

See this post to find the backtick on your keyboard. The “preformatted text” tool in the editor (</>) will also add backticks around text.

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