Overfitting: Overfitting is a phenomenon that can occur in machine learning when a model begins to “fit” the training data too closely, resulting in poorer performance on new data. This can be caused by excessive use of complex models or excessively large training sets, and can often be avoided by using more sophisticated cross-validation techniques during model selection.
Definition of Latent Class Analysis Latent Class Analysis: A technique used to identify unobserved (latent) classes within a population. How is a Latent Class Analysis used? Latent Class Analysis (LCA) is a statistical technique used to identify latent classes within data sets. These latent classes are clusters of data points with similar characteristics, which can…
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 Mean Mean: Mean is a mathematical calculation used to calculate the average of a set of numbers. How is the Mean used? The Mean is a statistical measure used in data analysis and machine learning to evaluate the central tendency of a given set of numerical values. It is calculated by adding up…
Definition of Data Frame Data Frame: A data frame is a rectangular table of data consisting of rows and columns. The data in each column has the same type, and the order of the columns is defined by the programmer. What is a Data Frame used for? A data frame is a two-dimensional data structure…
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).