Data Glossary Lab

Inference, is the operational phase where a trained statistical or machine learning model processes new, unseen data to produce a prediction, classification, or conclusion.

Interpretability in the context of data science and artificial intelligence refers to the degree to which a human being can comprehend the underlying cause or logic behind a machine learning model's decision.

Information Gain is a metric used in machine learning to measure the reduction of uncertainty or randomness in a dataset when it is split based on a specific feature.

An imbalanced dataset is a dataset used for classification tasks where the distribution of target classes is highly disproportionate.

Imputation is the process of replacing missing values with estimates or calculated values.