Non-negative matrix factorization (NMF)
Non-negative matrix factorization (NMF) is a mathematical technique used in data analysis and machine learning to decompose non-negative matrices into a product of non-negative factors.
data analysis
Fully parameterized quantile function (FQF)
The Fully Parameterized Quantile Function (FQF) is a statistical approach used to estimate quantiles across various distributions, enhancing flexibility in modeling.
Kernel method
The kernel method is a powerful technique used in machine learning and statistical analysis for pattern recognition and data transformation.
Causal graph
A causal graph is a visual representation of causal relationships among variables, often used in statistics and data analysis.
Logistic regression
Logistic regression is a statistical method for predicting binary classes. It models the probability of a certain class or event occurring.
Logit lens
The Logit lens is a statistical tool used in various fields to model and analyze categorical outcomes. It is particularly significant in fields like economics, healthcare, and social sciences.
Laplacian eigenmaps
Laplacian eigenmaps is a dimensionality reduction technique used in machine learning and data analysis, particularly for nonlinear data structures.
Principal component analysis (PCA)
Principal component analysis (PCA) is a statistical technique used to reduce the dimensionality of data by transforming it into a new set of variables called principal components. These components capture the maximum variance within the data, enabling easier visualization, interpretation, and noise reduction.
Dimensionality reduction
Dimensionality reduction is a process in data analysis and machine learning that transforms data from a high-dimensional space into a lower-dimensional space while preserving essential properties. It facilitates visualization, reduces storage requirements, and helps improve the performance of algorithms by eliminating redundant or irrelevant features.
OPTICS algorithm
The OPTICS (Ordering Points To Identify the Clustering Structure) algorithm is a density-based clustering method that identifies clusters of varying shapes and sizes in large datasets.