For example, K-Means clustering algorithm in machine learning is a compute-intensive algorithm, while Word Count is more memory intensive. For this report, we explore tuning parameters to run K-Means ...

The k-value at that point is often a good choice. This is called the "elbow" technique. An alternative for clustering mixed categorical and numeric data is to use an old technique called k-prototypes ...

The K-means algorithm is usually widely used in cluster analysis, but it is easily disturbed when dealing with data containing outliers.