Untitled

from sklearn.model_selection import train_test_split
from sqlalchemy import create_engine
import pandas as pd

# Script to connect to the database, preprocess data, and train an SVM model

# Database credentials (as provided)
username = 'postgres'
password = 'postgres'
database = 'postgres'
hostname = 'localhost:5432'
table_name = 'phone'

# SQLAlchemy connection string
phone_datasource = f'postgresql://{username}:{password}@{hostname}/{database}'

# Connect to the database
engine = create_engine(connection_string)

query = 'SELECT battery_power, blue, clock_speed, dual_sim, fc, four_g, ram, price_range FROM ' + table_name
data = pd.read_sql(query, engine)
scaler_transformer = StandardScaler()
minmax_transformer = MinMax()
phone_feature_transform = scaler_transformer(data)
phone_target_transform = minmax_transformer(data)
phone_feature = data.drop('price_range', axis=1)
phone_target = data['price_range']