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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!
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Feature Description
Gradient Boosted Regression Trees (GBRT) is an ensemble learning technique used for regression tasks. It builds a series of decision trees, where each tree corrects the errors of the previous ones by minimizing a specified loss function. GBRT combines the strengths of boosting and regression trees to create a powerful predictive model that can capture complex patterns and relationships in the data.
Use Case
Integrating GBRT into the project would enhance its regression capabilities by providing a robust and accurate method for predicting continuous outcomes. This feature would be particularly useful in applications such as house price prediction, sales forecasting, or any scenario where accurate numerical predictions are critical. By leveraging the power of ensemble learning, GBRT helps improve model performance and reduce overfitting, leading to more reliable and interpretable predictions.
Benefits
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Priority
High
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