EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions.
Open source
24 alternativesmlforgex
github.com/dhgefergfefruiwefhjhcduc/ML_Forgex
ML Training & Optimization
Open-source projectOpen source
ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.
About mlforgex
mlforgex is an open-source Python package for automated machine learning (AutoML). It trains, evaluates, and runs predictions with machine learning models on cleaned datasets, and it is designed to reduce the boilerplate code needed for these steps. According to the repository, a short script can produce a trained pipeline and an interactive HTML dashboard of model performance. It is available on PyPI.
The package detects whether a task is regression or classification and trains several algorithms, including XGBoost and LightGBM. It also includes preprocessing, imbalance handling, a text-processing mode for NLP tasks, and ensemble construction. Saved model and preprocessor files can be reused to make predictions on new data. The package requires Python 3.8 or higher. The homepage excerpt does not describe features for cloud use or data privacy, and advanced usage is covered in external documentation.
Key features
- Detects regression or classification and trains models such as XGBoost and LightGBM
- Built-in preprocessing for outliers, skewed features, correlated features, and encoding
- Imbalance handling using random under-sampling or SMOTETomek
- NLP mode with tokenization, stopword removal, lemmatization, and Word2Vec embeddings
- Stacking and voting ensembles built from top-performing tuned models
- Generates a Plotly HTML dashboard with feature importance, heatmaps, and metric curves
Best for: Python developers and data practitioners who want to train and evaluate models on cleaned CSV datasets, including text data, with minimal setup code.
Good for
- Installable with pip from PyPI
- Offers both a Python API and a command line interface
- Open source
Watch out for
- Requires Python 3.8 or higher
mlforgex at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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mlforgex FAQ
How do I install mlforgex?
Install it from PyPI with pip install mlforgex. It requires Python 3.8 or higher.
How are predictions made after training?
Training saves model.pkl and preprocessor.pkl in the artifacts directory. The predict_data function can then load these files and generate predictions for new data.
Is there a command line option?
Yes. The mlforgex-train and mlforgex-predict commands train models and generate predictions from the terminal.
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