1) Select the intention of the following machine learning algorithms: from sklearn.neighbors import KNeighborsClassifier classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2) classifier.fit(X_train, y_train) kmeans = KMeans(n_clusters = 5, init = 'k-means++', random_state = 42) y_kmeans = kmeans.fit_predict(X) Group of answer choices a. overfit the data for classification and underfit the data for the clustering b. Look for 5 closest neighbors and form 5 clusters c. Only form 5 clusters d. underfit the data for classification and overfit the data for the clustering

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System Model Approaches

The systems model approach is a process-oriented representation that emphasizes the impact or flow of information between modules. The multidisciplinary study of the use of models to design and create systems in business and IT development is known as systems model approach. It models how processes interact and what these processes do, but it does not go into detail about how these processes are implemented. Functional decomposition may be utilized to enhance the models employed in this technique, and they can be coupled to requirements models for additional system partitioning.