search

JasonDCox / ML-Mentorship-GovSchool

0 stars 0 forks source link

Implement Ensemble kNN Classifier #13

Closed gavinjalberghini closed 2 years ago

gavinjalberghini commented 3 years ago

Description: By this point, we have refined our basic kNN algorithm. Now we can begin to make improvements based on what we are learning. To kick off this process, we will start with implementing an ensemble of kNN classifiers. You will remember in #2 that there are various means of leveraging ensemble learning to improve performance.

For this issue, implement an ensemble of three kNNs. Have each kNN utilize a different distance calculation from your previous implementation. Be sure to think about how to reconcile the output of each classifier into one prediction.

Acceptance Criteria: Create a new implementation names /kNN_ensemble.py that outputs the information from all classifiers as well as the final combined confusion matrix into a file named /output_ensemble.py

JasonDCox commented 2 years ago

Complete - Jason

gavinjalberghini commented 2 years ago

Jason plans to take a second pass at this implementation over the weekend.