# Overfitting

Overfitting : Overfitting is a phenomenon that occurs when a machine learning model becomes too complex and adapts too closely to the specific training data it was given, resulting in poor generalization to new data. This can lead to poor performance on unseen data and can ultimately hinder the model’s ability to accurately predict outcomes. […]

# Outlier

Outlier : An outlier is a data point that is significantly different from the other data points in a dataset. It can be caused by a variety of factors, including errors in measurement, extreme values, or simply being an unusual occurrence. Outliers can have a significant impact on the results of statistical analyses, so it […]

# Outcome

Outcome : Outcome refers to the result or consequence of a particular action or series of actions. It can be a positive or negative outcome, depending on the nature of the action and the desired result. Outcomes can be influenced by a variety of factors, including the individual or group taking the action, the environment […]

# Orthogonal matrix

Orthogonal matrix : An orthogonal matrix is a type of matrix that has several important properties. In general, an orthogonal matrix is a square matrix with real-valued entries that satisfies the property that its transpose is equal to its inverse. This means that if a matrix is orthogonal, then its rows are orthogonal to its […]

# Orthogonal

Orthogonal : Orthogonal is a term used to describe a relationship between two things that are perpendicular to each other. This can be seen in geometry, where two lines are said to be orthogonal if they are perpendicular to each other, and in mathematics, where two vectors are orthogonal if they are perpendicular to each […]

# Orthant probability

Orthant probability : Orthant probability is a concept in mathematics that refers to the probability of a multivariate random vector falling within a particular region in space. In other words, it is the probability that all of the variables in a vector will fall within certain ranges or limits. One example of orthant probability is […]

# Ordination

Ordination : Ordination is a statistical method used in data science to visualize and analyze the relationships among variables in a dataset. It is often used in the fields of ecology, sociology, and psychology to identify patterns and trends in data. There are several different techniques that can be used for ordination, including principal components […]

# Ordinal Variable

Ordinal Variable : An ordinal variable is a type of categorical variable in which the categories can be ranked or ordered in a specific way. This means that there is a clear hierarchy or hierarchy of the categories, with one category being higher or lower than the other. Ordinal variables are commonly used in social […]

# Ordered alternative hypothesis

Ordered alternative hypothesis : An ordered alternative hypothesis is a statistical hypothesis that proposes a specific order or ranking among a set of variables or groups. It is commonly used in situations where there is a need to compare the relative magnitude or importance of different factors or variables. For example, consider a study on […]

# Oracle property

Oracle property : The Oracle property, also known as the Oracle estimator, refers to a statistical estimator that is assumed to have perfect knowledge of the true underlying distribution or population from which a sample is drawn. In other words, an Oracle estimator is a hypothetical statistical estimator that is able to make the most […]