In a supervised machine learning dataset, what is the term used for the variable that the model aims to predict based on the input variables?
Feature
Parameter
Label
Hyperparameter
Label - This is the correct answer. In supervised machine learning, the label is the target variable that the model aims to predict based on the input variables (features). For example, in a dataset predicting house prices, the house price would be the label.
Feature - A feature is an input variable (predictor) used by the model to make predictions. Features are the independent variables in the dataset that help determine the value of the label.
Parameter - A parameter refers to the internal variables of a model that are learned during training, such as the weights in a neural network. Parameters are not the target variable but the model's learned coefficients.
Hyperparameter - A hyperparameter is a setting that is manually chosen before training a model (such as the learning rate or the number of trees in a random forest) but is not part of the dataset itself. Hyperparameters control the learning process and model configuration.
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
All Information Technology Package plans include the following perks and exams.
Our pricing is simple. Full access to all certifications and exams in each package, for one price.
As many practice tests for as many topics as you want.
Use study mode non-stop, no limits.
Access to our AI assistant, Bash, trained to help you pass your exam.
Track your scores over time in study mode and report cards.
See how you improve over time, and where you need to focus.
Access our store with even bigger discounts than before.
Unlimited access to all performance questions and be prepared for the real thing.
All Information Technology Package plans include unlimited access to the following study materials.
Create an account or sign in to access our study materials.