An automated machine learning optimization package
Project description
Aion Optimizer
A Python package for automated machine learning optimization.
Installation
pip install aion_optimizer
Usage
from aion_optimizer import EnhancedSequentialOptimizer
import pandas as pd
from sklearn.model_selection import train_test_split
dataset_path = "..."
df = pd.read_csv(dataset_path)
optimizer = EnhancedSequentialOptimizer(
task_type='classification',
target_column='class',
generations=5,
cv_folds=5,
random_state=42,
n_jobs=-1,
verbosity=0,
categorical_threshold=10
)
train_df, test_df = train_test_split(df, test_size=0.2, random_state=42)
# Fit the optimizer
optimizer.fit(train_df)
# Get the best model parameters and print them
results = optimizer.best_model_params(test_df)
print(results)
## Features
- Automatic model selection
- Hyperparameter optimization
- Support for:
- Binary classification
- Multiclass classification
- Regression
- Simplified metrics reporting
- Cross-validation support
- Detailed results logging
## Requirements
- Python >=3.7
- NumPy >=1.19.0
- Pandas >=1.2.0
- Scikit-learn >=0.24.0
- SciPy >=1.6.0
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