pycodeml 0.0.9

Automatically train multiple regression models and return the best one.

PyCodeml

PyCodeml is a Python package designed to automate the training, evaluation, and selection of the best-performing machine learning models for regression and classification tasks. It simplifies the process of model training, comparison, and deployment.

Features

✅ Supports Regression and Classification tasks
✅ Evaluates multiple models and selects the best one
✅ Saves and loads trained models for future use
✅ Simple and intuitive API

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Installation

You can install PyCodeml using pip:

pip install pycodeml

Usage

1️⃣ Train and Save the Best Model

import pandas as pd
from PyCodeml.regressor import RegressorTrainer  # For regression tasks

# Load dataset from a CSV file (Ensure "target" column exists)   you can give another name to target col 
df = pd.read_csv("data.csv")

# Initialize and train the model
trainer = RegressorTrainer(df, "target")
best_model = trainer.train_and_get_best_model()

# Save the best model
trainer.save_best_model("best_model.pkl")

2️⃣ Load and Use the Saved Model

import pandas as pd
import numpy as np
from PyCodeml.utils import load_model

# Load the saved model
model = load_model("best_model.pkl")

# Load new data from a CSV file (without target column)
new_data = pd.read_csv("new_data.csv")

# Ensure the new data has the same feature columns as the training data
# (Make sure "new_data.csv" has the same structure as the training dataset)
prediction = model.predict(new_data)

# Print the predictions
print("Predicted Values:", prediction)

Supported Models

Regression

• Linear Regression
• Decision Tree Regressor
• Random Forest Regressor
• Support Vector Machine (SVR)
• Gradient Boosting Regressor
• Ridge Regression
• Lasso Regression
• Elastic Net

Classification (Coming Soon)

• Logistic Regression
• Random Forest Classifier
• Support Vector Machine (SVM)
• Gradient Boosting Classifier
• K-Nearest Neighbors (KNN)

Contributing

Contributions are welcome! If you’d like to improve this package, feel free to fork the repository and submit a pull request.
https://github.com/Nachiket858/PyCodeML