Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Declare Feature Vector and Target Variable | Clustering Demystified
Clustering Demystified
course content

Conteúdo do Curso

Clustering Demystified

bookDeclare Feature Vector and Target Variable

A feature vector is a set of numerical features that represent an object or sample. In machine learning, a feature vector is used as input to a model, and it typically contains multiple features that describe the characteristics of the object.

A target variable, also known as a response or dependent variable, is the variable that the model is trying to predict. It is the output of the model, and it is typically a numerical or categorical value.

For example, in a supervised learning problem where we want to predict the price of a house, the feature vector might include things like the number of bedrooms, square footage, and neighborhood, while the target variable would be the price of the house.

Methods description

The indexing [] operator is used to select specific columns from the DataFrame. For example, data[column_name] retrieves the column named "column_name" from the DataFrame data.

Tarefa

  1. Declare feature vector (entire data).
  2. Declare the target variable ("status_type" column).

Mark tasks as Completed
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

A feature vector is a set of numerical features that represent an object or sample. In machine learning, a feature vector is used as input to a model, and it typically contains multiple features that describe the characteristics of the object.

A target variable, also known as a response or dependent variable, is the variable that the model is trying to predict. It is the output of the model, and it is typically a numerical or categorical value.

For example, in a supervised learning problem where we want to predict the price of a house, the feature vector might include things like the number of bedrooms, square footage, and neighborhood, while the target variable would be the price of the house.

Methods description

The indexing [] operator is used to select specific columns from the DataFrame. For example, data[column_name] retrieves the column named "column_name" from the DataFrame data.

Tarefa

  1. Declare feature vector (entire data).
  2. Declare the target variable ("status_type" column).

Mark tasks as Completed
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 1. Capítulo 5
AVAILABLE TO ULTIMATE ONLY
some-alt