{"id":5311,"date":"2021-09-02T13:43:40","date_gmt":"2021-09-02T08:13:40","guid":{"rendered":"https:\/\/www.goseeko.com\/blog\/?p=5311"},"modified":"2025-12-29T11:11:48","modified_gmt":"2025-12-29T05:41:48","slug":"what-is-supervised-learning","status":"publish","type":"post","link":"https:\/\/www.goseeko.com\/blog\/what-is-supervised-learning\/","title":{"rendered":"What is Supervised Learning?"},"content":{"rendered":"\n

As the name implies, supervised learning<\/a> involves the presence of a supervisor who also serves as an instructor. In a nutshell, supervised learning (SL)is when we instruct or train a machine using well-labeled data. This signifies that some information has already been label with the correct answer. The machine is then gave a new collection of examples (data) to analyze the training data (set of training examples) and produce a proper result from label data using these method. <\/p>\n\n\n\n

It is a sort of machine learning in which machines are train using well-labeled training data and then predict the output based on that data. The label data indicates that some of the input data has already tagged with the appropriate output.<\/p>\n\n\n\n

In these, the training data presented to the machines acts as a supervisor, instructing the machines on how to correctly predict the output. It uses the same notion as when a student learns under the guidance of a teacher.<\/p>\n\n\n\n

Types <\/strong>of supervised learning<\/h2>\n\n\n\n

There are two types of algorithms for this learning:<\/p>\n\n\n\n

Regression<\/strong>  – When the output variable is a real value, such as “dollars” or “weight,” a regression problem exists. If there is a relationship between the input and output variables, regression procedures are apply. It’s uses to predict continuous variables like weather forecasting, market trends, and so on. <\/p>\n\n\n\n

Classification<\/strong>  – When the output variable is a category, such as “Red” or “Blue,” or “illness” and “no disease,” the problem is called a classification problem.<\/p>\n\n\n\n

When the output variable is categorical, meaning there are two classes, Olxslot Gacor<\/a> such as Yes-No, Male-Female, True-False, and so on, classification methods are utilize.<\/p>\n\n\n\n

Advantages  <\/strong><\/h2>\n\n\n\n