github-actions[bot]
commented
1 month ago Hi @pavitraag! Thanks for opening this issue. We appreciate your contribution to this open-source project. Your input is valuable and we aim to respond or assign your issue as soon as possible. Thanks again!
Is there an existing issue for this?
Feature Description
Gradient Boosting Machines (GBM) are a powerful ensemble learning technique that combines the predictions of multiple weak learners (typically decision trees) to form a strong predictive model. The core idea is to build models sequentially, with each new model attempting to correct the errors made by the previous models. GBM is highly effective for both regression and classification tasks, known for its robustness and ability to handle various types of data.
Use Case
Integrating a GBM module will enhance the project's capability by providing a robust tool for building and optimizing predictive models, thus aiding in tasks like financial forecasting, medical diagnosis, and customer behavior analysis, while offering insights into feature significance and model performance.
Priority
High
Record