Open Source
Definition of Open Source Open Source: Open source refers to software for which the original source code is made freely available and may be redistributed and modified.
One-hot encoding
Definition of One-hot encoding One-hot encoding: One-hot encoding is a technique used in machine learning to represent categorical variables as a vector of binary values. In one-hot encoding, each category is represented by a unique integer value, and the remaining values are set to 0. For example, if there are three categories, A, B, and…
Octile
Definition of Octile Octile: An octile is a statistical value that divides a set of data into eight equal parts.
Observational Study
Definition of Observational Study Observational Study: Observational study is a study in which data is collected without affecting the participants.
Oblique Sampling
Definition of Oblique Sampling Oblique Sampling: Oblique sampling is a type of non-random sampling technique. It is used when the researcher wants to study a specific population but does not have access to all members of that population. Oblique sampling involves selecting units for the study in a way that is not completely random. The…
Oblique Rotation
Definition of Oblique Rotation Oblique Rotation: Oblique rotation is a type of rotation that is not perpendicular to the plane of rotation.
Numerical
Definition of Numerical Numerical: Numerical data is data that can be represented as a number. This type of data is often used in statistics and machine learning.
Normalized
Definition of Normalized Normalized: Normalized is a statistic term referring to the process of adjusting a value to have a unit of measurement. For example, the value of weight can be normalized by dividing it by the unit of weight, such as kilograms.
Normalization
Definition of Normalization Normalization: Normalization is the process of standardizing data so that it has a consistent meaning across different data sets. This can be done by ensuring that all values in a data set are within a certain range, or by converting all data to a single numerical representation. Normalization can make it easier…
Non-Negative Matrix Factorization
Definition of Non-Negative Matrix Factorization Non-Negative Matrix Factorization: Non-negative Matrix Factorization (NMF) is a technique used to decompose a matrix into two parts: a lower triangular matrix (containing the “feature” values) and an upper triangular matrix (containing the “coefficients” associated with each feature).