Which of the following is NOT a common method for data classification?Naive BayesK-Means ClusteringDecision TreesRegression Analysis

To identify which of the following options is NOT a common method for data classification, let's analyze each one:

1. Naive Bayes: This is a probabilistic classification technique based on Bayes' theorem. It is widely used for classification tasks, particularly in text classification.

2. K-Means Clustering: This is primarily an unsupervised learning algorithm used for clustering, not classification. While it groups data into clusters, it does not assign labels to new instances based on a training dataset.

3. Decision Trees: This is a common method for both classification and regression tasks. It works by splitting data into branches based on feature values, making predictions based on the majority class in each terminal node.

4. Regression Analysis: This method primarily focuses on predicting a continuous outcome variable rather than classifying data into distinct categories. It is not regarded as a classification technique.

Conclusion

Based on this analysis, K-Means Clustering is NOT a common method for data classification, as it is used for clustering rather than assigning labels to classes.