Stanford Classifier
The Stanford Classifier is a Java-based maximum entropy classifier designed for categorizing data into multiple classes. It excels with text data while also accommodating numeric variables, providing a probability distribution for class assignments. Offering both a command-line interface and API access, it is available under the GNU General Public License, promoting flexible use and collaboration.
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Top Stanford Classifier Features
- Probabilistic class assignment
- Java implementation
- Maximum entropy classifier
- Softmax classifier equivalent
- Suitable for text data
- Supports numeric variables
- Easy command-line interface
- Open source licensing
- Commercial licensing available
- Includes example files
- Comprehensive documentation
- Lightweight download size
- Community mailing lists
- User support via Stack Overflow
- Feature request discussions
- Annual update announcements
- Flexible usage options
- Designed for sparse data
- Maintenance through gift funding
Top Stanford Classifier Alternatives
- ibm powerai
- OpenAI Gym
- IBM Machine Learning for z/OS
- The Libra Toolkit
- Apache SAMOA
- SAS Factory Miner
- Apache SystemML
- PyTorch
- FlinkML
- Accord.MachineLearning
- Amazon CodeGuru
- PushGP
- Simple Bayes
- Theano
- Classifier
