Type II Error
Definition of Type II Error
Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.
Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.
Definition of K-means clustering K-means clustering: K-means clustering is a data mining algorithm used to partition a set of data points into k clusters. Data is divided into clusters based on the similarities of the points within each cluster. This algorithm is often used to segment customers into different groups for marketing purposes. How is…
Definition of T-distribution The t-distribution is a type of probability distribution that is used to calculate the likelihood of an event occurring. It is a bell curve-like distribution that is used to calculate the standard error of a statistic.
Definition of Feature Engineering Feature Engineering: Feature engineering is the process of transforming raw data into a form that is more amenable to analysis or machine learning. This can involve things like aggregating data, transforming variables, or creating new features from existing variables. Feature engineering is an important part of data science, as it can…
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