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import streamlit as st | |
import joblib | |
import pandas as pd | |
import numpy as np | |
import plotly.graph_objects as go | |
from PIL import Image | |
import time | |
import matplotlib.pyplot as plt | |
from io import BytesIO | |
# Load the saved trained models, transformers, and the scalers | |
num_imputer = joblib.load('https://drive.google.com/file/d/1qdh31R8f7KzP3UZY9rZkMUrtxDbX69sr/view?usp=drive_link/numerical_imputer.joblib') | |
cat_imputer = joblib.load('https://drive.google.com/file/d/1qdh31R8f7KzP3UZY9rZkMUrtxDbX69sr/view?usp=drive_link/cat_imputer.joblib') | |
encoder = joblib.load('https://drive.google.com/file/d/1qdh31R8f7KzP3UZY9rZkMUrtxDbX69sr/view?usp=drive_link/encoder.joblib') | |
scaler = joblib.load('https://drive.google.com/file/d/1qdh31R8f7KzP3UZY9rZkMUrtxDbX69sr/view?usp=drive_link/scaler.joblib') | |
lr_model = joblib.load('https://drive.google.com/file/d/1qdh31R8f7KzP3UZY9rZkMUrtxDbX69sr/view?usp=drive_link/lr_smote_model.joblib') | |