|
|
| import pandas as pd |
| from sklearn.linear_model import LogisticRegression |
| from sklearn.model_selection import train_test_split |
| import joblib, os |
|
|
| print("===== STEP 1: Load Data =====") |
|
|
| data = pd.DataFrame({ |
| "Age":[25,45,33,52,23,40,60,48], |
| "Balance":[1000,5000,2300,8000,1200,4500,9000,3000], |
| "Exited":[0,1,0,1,0,1,1,0] |
| }) |
|
|
| print("Dataset ready") |
|
|
| print("===== STEP 2: Train Model =====") |
|
|
| X=data[["Age","Balance"]] |
| y=data["Exited"] |
|
|
| X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2) |
|
|
| model=LogisticRegression() |
| model.fit(X_train,y_train) |
|
|
| os.makedirs("models",exist_ok=True) |
| joblib.dump(model,"models/pipeline.joblib") |
|
|
| print("Model saved to models/pipeline.joblib") |
| print("Pipeline finished") |
|
|
