A novel algorithmic system that works subtly in the background to mutual benefit, and adapts quickly to local conditions, ...

The dataset is carefully chosen, and various steps including collecting data, preparing it through preprocessing, extracting significant features, and developing a model using the K-Nearest Neighbors ...

Evaluation: Evaluate the performance of the KNN algorithm on the testing set, and use the results to determine the optimal value for k and adjust the algorithm as needed.

In recent years, the interest in using machine learning to solve complex problems in different sectors using parallel algorithms has increased. The KNN algorithm is the most popular method to classify ...

The weighted k-NN classification algorithm has received increased attention recently for two reasons. First, by using neural autoencoding, k-NN can deal with mixed numeric and non-numeric predictor ...