GSoC'24 Progress: Nearing Completion on ClassificationGAM

Hello Everyone,

I'm excited to share the latest developments in my project. Over the past few weeks, I've made significant strides. Here's a summary of what's been happening:

I've successfully developed the 'ClassificationGAM' class, which introduces generalized additive models (GAMs) to our toolkit. GAMs are instrumental in capturing non-linear relationships between features and the target variables, offering a powerful alternative to linear models. The 'ClassificationGAM' class I implemented uses gradient boosting with spline fitting as the base learner, enabling the model to effectively capture complex patterns in the data. I'm currently working on the 'predict' method, allowing the model to make accurate predictions based on the learned relationships.

After completing the 'predict' method for 'ClassificationGAM', I will focus on adding documentation for the 'ClassificationDiscriminant' class's fit method and 'ClassificationGAM' class. Additionally, I'll modify the existing demos of the 'fitcdiscr' by incorporating plots to visualize the results, which will help users better understand the models' capabilities.

I'll also be developing tests and demos to validate the functionality of the 'ClassificationGAM' class. These tests are essential to ensure that the models perform as expected across different scenarios. 

Thank you for following my progress as I near the completion of this exciting journey.

Stay tuned for more updates.

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