A PySpark package that that implements Kernel SVM classification based on the Cascading SVM idea presented in [1].
Note that currently the implementation only runs on single machines (though on multiple cores), as we are not distributing the model object for prediction.
To install the cvm package, simply run
pip install .
To install the cvm package in development mode, run
pip install -e .
To obtain the data, run the ./get_data.sh script.
In this example, we classify the handwritten digit.
From the top level directory, run
[SPARKDIR]/bin/spark-submit --driver-memory 2g bin/mnist.py
In this example, we try to classify whether the forest covertype is of type 2 or not, such that the problem becomes a binary classification problem.
From the top level directory, run
[SPARKDIR]/bin/spark-submit --driver-memory 2g bin/covertype.py
- Carlos Riquelme
- Lan Huong
- Sven Schmit
[1] Graf, Hans P., Eric Cosatto, Leon Bottou, Igor Dourdanovic, and Vladimir Vapnik. "Parallel support vector machines: The cascade svm." In Advances in neural information processing systems, pp. 521-528. 2004.