prediction

Prediction refers to the output of a machine learning model when given new, unseen data. More specifically, prediction is the process of using a trained machine learning model to estimate or forecast a target variable based on input features.

The model learns patterns and relationships from historical training data, and then uses this learning to generate predicted values for new data points. The purpose of prediction in machine learning is to make informed guesses about probable outcomes, helping organizations forecast future trends, behaviors, and requirements to drive data-driven decisions.

Citations:

[1] https://h2o.ai/wiki/prediction/

[2] https://www.javatpoint.com/machine-learning-prediction

[3] https://datascience.stackexchange.com/questions/42957/whats-the-difference-between-the-terms-predictor-and-feature

[4] https://www.linkedin.com/advice/0/how-can-you-generate-predictions-recommendations-classifications

[5] https://towardsdatascience.com/classification-regression-and-prediction-whats-the-difference-5423d9efe4ec

[6] https://www.techtarget.com/searchenterpriseai/definition/predictive-modeling

[7] https://hbr.org/2020/09/how-to-win-with-machine-learning

[8] https://www.sas.com/en_gb/insights/articles/analytics/a-guide-to-predictive-analytics-and-machine-learning.html