PLEASD stands for Prediction and LEArning for Structured Data. It is a Matlab toolbox of algorithmic frameworks for training structured prediction models. We provide this toolbox to ease the process of applying structured learning to new problems. We attempt to minimize users’ involvement in coding the structured learning framework such that they can focus on issues related to their specific problems. Currently, PLEASD has included the following structured learning frameworks: 1. Bundle method for risk minimization; 2. Structured perceptron learning; 3. Structured learning from partial annotations; 4. Structured perceptron learning from partial annotations.
- Changes to previous version:
Initial Announcement on mloss.org.
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