pycodeml 0.0.16

Automatically train multiple regression models and return the best one.

PyCodeML

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

✅ Features

• Supports Regression and (soon) Classification tasks
• Evaluates multiple models and selects the best one
• Hyperparameter tuning support for optimized performance
• Saves and loads trained models for future use
• Simple and intuitive API for fast prototyping and deployment

📦 Installation

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)
df = pd.read_csv("data.csv")

# Initialize and train the model
trainer = RegressorTrainer(df, "target", data_sample_percent=100)
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
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")

# Make predictions
prediction = model.predict(new_data)
print("Predicted Values:", prediction)

3️⃣ Tune the Best Model

from pycodeml.tunner import RegressorTuner

# Perform hyperparameter tuning on the best model
tuner = RegressorTuner(
    model=best_model,
    dataset=df,
    target_column="target",
    model_name="Random Forest"  # Must match one of the supported models
)

# Get the tuned model
tuned_model,score = tuner.tune()

📊 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

• 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.

🔗 GitHub: https://github.com/Nachiket858/PyCodeML