Marketing Prediction
Bank Deposits Prediction Model
Function get_data():
Input | Type | Description |
---|---|---|
training dataset | url<string> | URL of a training CSV file |
testing dataset | url<string> | URL of a testing CSV file |
Returns pandas.dataframe, pandas.dataframe
Usage
Function preprocess_inputs():
Input | Type | Description |
---|---|---|
training dataset | *pandas.dataframe* | Model training dataset in dataframe |
testing dataset | *pandas.dataframe* | Model testing dataset in dataframe |
model_name | string | Model name as a string Default = "Logistic_Regression" | "Support_Vector_Machine" "Support_Vector_Machine_Optimized" "Decision_Tree" "Neural_Network" "Random_Forest" |
Returns pandas.dataframe, pandas.dataframe
Usage
Function pretrained():
Input | Type | Description |
---|---|---|
model_name | string | Model name as a string Default = "Logistic_Regression" | "Support_Vector_Machine" "Support_Vector_Machine_Optimized" "Decision_Tree" "Neural_Network" "Random_Forest" |
Returns model
Usage
Function train():
Input | Type | Description |
---|---|---|
training dataset | *pandas.dataframe* | Model training dataset in dataframe |
testing dataset | *pandas.dataframe* | Model testing dataset in dataframe |
model_name | string | Model name as a string Default = "Logistic_Regression" | "Support_Vector_Machine" "Support_Vector_Machine_Optimized" "Decision_Tree" "Neural_Network" "Random_Forest" |
Returns model
Usage
Function predict():
Input | Type | Description |
---|---|---|
test dataset | *pandas.dataframe* | Model test dataset in dataframe |
model | function() | Model function from pretrained / train |
Returns array
Usage
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