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To implement a simple K-Means algorithm for clustering in the context of *Computer Networks and Data Mining*, we can use Python with the help of libraries like `scikit-learn` and `scipy`. The `.arff` (Attribute-Relation File Format) datasets such as `iris.arff` and `student.arff` can be processed using `scipy.io.arff`. These datasets will be used to demonstrate how K-Means groups data based on similarity, which is a core concept in unsupervised learning for tasks such as anomaly detection in networks and user behavior segmentation in data mining. First, we load the datasets. Using the `scipy.io.arff.loadarff()` function, we can read `.arff` files into a format ______ _________ _________ __________ _________ ___ ________ __________.
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