What is a target attribute?
A target attribute, also known as a target variable or response variable, is a specific attribute or column in a dataset that represents the outcome or prediction target in a supervised learning problem. In supervised learning, the goal is typically to predict or model the value of the target attribute based on the values of other attributes, known as predictor variables or features.
For example, in a dataset of housing prices, the target attribute might be the sale price of houses, while the predictor variables could include attributes such as the number of bedrooms, the square footage, and the location. The target attribute is what the model aims to predict or estimate based on the input features.
Understanding Data Attribute Types | Qualitative and Quantitative
When we talk about data mining, we usually discuss knowledge discovery from data. To learn about the data, it is necessary to discuss data objects, data attributes, and types of data attributes. Mining data includes knowing about data, finding relations between data. And for this, we need to discuss data objects and attributes.
Data objects are the essential part of a database. A data object represents the entity. Data Objects are like a group of attributes of an entity. For example, a sales data object may represent customers, sales, or purchases. When a data object is listed in a database they are called data tuples.
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