Identity Matrix
Identity Matrix : An identity matrix is a square matrix with ones on the main diagonal and zeros everywhere else. It is also called an identity element or unit matrix. The identity matrix is denoted by the symbol “I” or “1”. The identity matrix has several important properties. First, it is always a square matrix, […]
Idempotent Matrix
Idempotent Matrix : In linear algebra, an idempotent matrix is a square matrix that, when multiplied by itself, yields itself as the result. In other words, it is a matrix that satisfies the equation A^2 = A. One example of an idempotent matrix is the identity matrix, which is a square matrix with 1s on […]
Hypothesis Testing
Hypothesis Testing : Hypothesis testing is a statistical method used to determine whether or not a certain hypothesis about a population is true. It is an essential tool in statistical analysis, and is used to make decisions about a population based on sample data. To understand hypothesis testing, let’s first define some key terms. The […]
Hypothesis
Hypothesis : A hypothesis is a proposed explanation for a phenomenon or a set of observations. It is a testable statement that is used to help explain a phenomenon or to make predictions about future events. Hypotheses are essential in the scientific process because they help scientists to test their theories and to gather evidence […]
Hyperplane
Hyperplane : A hyperplane is a subspace of one dimension less than the space it is embedded in. In other words, a hyperplane is a flat surface that divides a higher-dimensional space into two or more distinct regions. For example, in a two-dimensional space, a line can be thought of as a hyperplane as it […]
Hyperparameter Tuning
Hyperparameter Tuning : Hyperparameter tuning is the process of adjusting the hyperparameters of a machine learning model to optimize its performance on a specific dataset. This process is essential to achieving the best possible results from a model and can be critical to the success of a machine learning project. One example of hyperparameter tuning […]
Hyperparameter
Hyperparameter : Hyperparameters are a type of parameter in machine learning algorithms that cannot be directly learned from the data. They are set prior to training the model and are used to control the behavior of the learning algorithm. One example of a hyperparameter is the learning rate in a neural network. The learning rate […]
Hyperbolic distributions
Hyperbolic distributions : A hyperbolic distribution is a type of probability distribution that is commonly used to model the behavior of complex systems or processes. This distribution is characterized by its heavy tails, which means that it has a higher probability of extreme values than other distributions. One example of a hyperbolic distribution is the […]
Huynh-Feldt correction
Huynh-Feldt correction : Huynh-Feldt correction is a statistical technique used to adjust the degrees of freedom in repeated measures designs. This correction is applied when the assumptions of sphericity, which is the assumption that the variances of the differences between all possible pairs of repeated measures are equal, are not met. One example of when […]
Hurdle Model
Hurdle Model : The hurdle model is a statistical model that is used to analyze the effect of multiple factors on a binary outcome. This model is often used in economics and marketing research to understand the factors that influence consumers’ decision-making process. For example, a company may use the hurdle model to understand the […]