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A company producing consumable goods wants to identify groups of people with similar tastes for the purpose of targeting different products for each group. You have to choose and apply an appropriate ML type for this problem. Which ONE of the following options represents the BEST possible solution for this above-mentioned task? SELECT ONE OPTION
Correct Answer: C
* A. Regression * Regression is used to predict a continuous value and is not suitable for grouping people based on similar tastes. * B. Association * Association is used to find relationships between variables in large datasets, often in the form of rules (e.g., market basket analysis). It does not directly group individuals but identifies patterns of co-occurrence. * C. Clustering * Clustering is an unsupervised learning method used to group similar data points based on their features. It is ideal for identifying groups of people with similar tastes without prior knowledge of the group labels. This technique will help the company segment its customer base effectively. * D. Classification * Classification is a supervised learning method used to categorize data points into predefined classes. It requires labeled data for training, which is not the case here as we want to identify groups without predefined labels. Therefore, the correct answer isCbecause clustering is the most suitable method for grouping people with similar tastes for targeted product marketing.
