Data Glossary Lab

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.

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

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.

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.