Akaike information criterion : Akaike information criterion, also known as AIC, is a statistical measure used to evaluate the quality of a model by comparing the goodness of fit of the model with the number of parameters in the model. The AIC is calculated by adding the residual sum of squares (RSS) and twice the […]

Alpha : Hyperparameter alpha refers to the smoothing parameter in the additive smoothing technique, which is a method of smoothing data in natural language processing and other fields. This technique is used to smooth out the impact of a particular word or event on the overall distribution of data, by adding a small amount of […]

Age-related reference ranges : Age-related reference ranges refer to the normal values of various laboratory tests and measurements that are specific to different age groups. These ranges provide a basis for interpreting test results and determining whether they fall within the normal range for a person’s age. For example, the normal range for hemoglobin in […]

Adam Optimisation : Adam (Adaptive Moment Estimation) is an optimization algorithm for training deep learning models. It is a variant of stochastic gradient descent (SGD) that uses moving averages of the parameters to provide a running estimate of the second raw moments of the gradients; the name Adam is derived from adaptive moment estimation. Adam […]

Activation Classification : Activation classification is a method used in machine learning to determine the output of a neural network. It is a way of categorizing the various activation functions used in neural networks, and it helps to understand how the neural network processes information. There are four main types of activation functions used in […]

Activation Function : Activation functions are a crucial part of neural networks, as they determine the output of a node or neuron in a neural network. Activation functions determine whether a neuron should be activated or not, based on the input received. Activation functions are essential in neural networks because they allow the network to […]

Accuracy Score : Accuracy score is a metric used to evaluate the performance of a classification model. It is the ratio of the number of correct predictions made by the model to the total number of predictions made. In other words, it measures the proportion of predictions made by the model that are correct. For […]

Adaptive Cluster Sampling : Adaptive cluster sampling is a type of sampling method that is used to select a sample from a population. This method is commonly used in surveys and research studies, as it allows for the selection of a representative sample from a population that is more efficient and cost-effective than other sampling […]

Actuarial statistics : Actuarial statistics is the branch of statistics that focuses on the analysis and modeling of uncertain events, particularly in the fields of insurance, finance, and pension planning. Actuaries use statistical techniques to assess the likelihood and impact of various risks, such as natural disasters, stock market fluctuations, and longevity. They use this […]

Acquiescence bias : Acquiescence bias is a form of response bias that occurs when individuals tend to agree with statements or questions, regardless of their accuracy or truthfulness. This tendency to agree with statements can lead to inaccurate responses and skewed data, resulting in unreliable research findings. One example of acquiescence bias can be seen […]