cognition, this pipeline can be adapted for: Facial recognition systems Medical image classification Speech recognition tasks Sensor data analysis Moreover, integrating other classifiers like SVM or Random Forests after PCA and LDA can further enhance performance. Conclu
ion or standardization functions. Weighted Voting: Assign weights to neighbors based on distance for more nuanced classification. Visualization: Plot decision boundaries and data distributions to interpret results. Pros and
identifying users with similar preferences, k-NN 2. source code helps generate personalized recommendations. Medical Diagnosis: k-NN implementations assist in classifying patient data to 3. predict diseases with high interpretability. In these applications, the simplicit
