We are working on enhancing our machine learning model's performance, and one key aspect is feature selection. Currently, we are looking for contributors to implement a feature selection algorithm that can help us identify the most relevant features for our predictive model.
Tasks:
Research and choose an appropriate feature selection algorithm (e.g., Recursive Feature Elimination, SelectKBest, LASSO regression,
etc.) based on our dataset and problem.
Implement the selected algorithm in Python, ensuring that it works efficiently with large datasets.
Test the feature selection algorithm on our dataset to identify the top N most relevant features .
Provide documentation and usage examples for the implemented algorithm.
Validate the algorithm's effectiveness by comparing model performance with and without feature selection.
Expected Outcome:
The implementation of this feature selection algorithm will significantly improve our model's performance and help us build more efficient and accurate predictive models in our AI/ML project.
We are working on enhancing our machine learning model's performance, and one key aspect is feature selection. Currently, we are looking for contributors to implement a feature selection algorithm that can help us identify the most relevant features for our predictive model.
Tasks:
Expected Outcome: The implementation of this feature selection algorithm will significantly improve our model's performance and help us build more efficient and accurate predictive models in our AI/ML project.