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(Created page with "{{see also|Machine learning terms}} ===Attribute in Machine Learning== An attribute, also referred to as a feature, is an identifiable property or characteristic of something being observed. In machine learning applications, attributes are employed to describe data instances or examples that feed into the model for training purposes. The objective is to extract meaningful and pertinent information from these attributes that can be used to make predictions about unseen da...")
 
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{{see also|Machine learning terms}}
{{see also|Machine learning terms}}
===Attribute in Machine Learning==
==Introduction==
An attribute, also referred to as a feature, is an identifiable property or characteristic of something being observed. In machine learning applications, attributes are employed to describe data instances or examples that feed into the model for training purposes. The objective is to extract meaningful and pertinent information from these attributes that can be used to make predictions about unseen data sets.
An attribute, also referred to as a feature, is an identifiable property or characteristic of something being observed. In machine learning applications, attributes are employed to describe data instances or examples that feed into the model for training purposes. The objective is to extract meaningful and pertinent information from these attributes that can be used to make predictions about unseen data sets.