What is the difference between supervised and unsupervised learning?(1 Point)Supervised learning requires labeled data while unsupervised learning does not.Unsupervised learning requires labeled data while supervised learning does not.Supervised learning does not require data while unsupervised learning does.There is no difference between supervised and unsupervised learning.
Question
What is the difference between supervised and unsupervised learning?(1 Point)Supervised learning requires labeled data while unsupervised learning does not.Unsupervised learning requires labeled data while supervised learning does not.Supervised learning does not require data while unsupervised learning does.There is no difference between supervised and unsupervised learning.
Solution
The difference between supervised and unsupervised learning lies in the type of data they require. Supervised learning requires labeled data. This means that the input data for a supervised learning algorithm includes both the features and the correct output. The algorithm uses this data to learn a model that can make accurate predictions.
On the other hand, unsupervised learning does not require labeled data. The input data for an unsupervised learning algorithm only includes the features, and the algorithm must find patterns and relationships within this data on its own. This can be used for tasks like clustering, where the goal is to group similar data points together.
So, the correct answer is: "Supervised learning requires labeled data while unsupervised learning does not."
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12. Which of the following statement correctly indicates the difference between ‘supervised learning’ and ‘unsupervised learning’?以下哪一個説法正確地指出「監督式學習」和「非監督式學習」的區別？Supervised learning cannot be applied to regression analysis, while unsupervised learning can. 監督式學習不可用於迴歸分析；非監督式學習則可以。Unsupervised learning requires a labeled dataset for training, while supervised learning can extract features and patterns from unlabeled dataset for learning. 非監督式學習需要利用已標注的數據集來進行學習；監督式學習則可以從未標注的數據集上歸納出特徵和模式。Supervised learning requires a labeled dataset for learning, while unsupervised can extract features and patterns from unlabeled dataset for learning. 監督式學習需要利用已標注的數據集來進行學習；非監督式學習則可以從未標注的數據集上歸納出特徵和模式。Supervised learning can be applied to clustering analysis, while unsupervised learning cannot. 監督式學習可用於分群分析；非監督式學習則不可以。
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