Hopfield Network is a form of recurrent artificial neural network. Hopfield networks are classical models of memory and collective processing in networks of abstract McCulloch-Pitts neurons, but they have not been widely used in signal processing as they usually have small memory capacity (scaling linearly in the number of neurons) and are challenging to train, especially on noisy data. Hopfield … Read more
Homoscedastic ‘in statistics, is a definition of a sequence or a vector of random variables if all random variables in the sequence or vector have the same finite variance. This is also known as the homogeneity of variance. The complementary notion is called heteroscedasticity’. Was the above useful? Please share with others on social media. If you want to look … Read more
Hierarchical Clustering in data mining and statistics (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types: Agglomerative: This is a “bottom up” approach: each observation starts in its own cluster, and pairs of clusters are merged as one moves … Read more
Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states. An HMM can be presented as the simplest dynamic Bayesian network. In simpler Markov models (like a Markov chain), the state is directly visible to the observer, and therefore the state transition probabilities are … Read more
Heteroscedasticity refers to the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it. In other words, it refers to data with unequal variability (scatter) across a set of second, predictor variables. Was the above useful? Please share with others on social media. If you want to look … Read more
Hash Table (Hash Map) in computing is a data structure used to implement an associative array, a structure that can map keys to values. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found. Ideally, the hash function will assign each key to a … Read more
Gini Coefficient is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation’s residents and is the most commonly used measure of inequality. The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income). A Gini coefficient of zero expresses perfect equality, where all values are the same … Read more
Gaussian Distribution (Normal Distribution) in probability theory is a very common continuous probability distribution. Normal distribution is important in statistics and is often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. The normal distribution is useful because of the central limit theorem. In its most general form, under some conditions (which … Read more
Fuzzy Clustering (also referred to as soft clustering) is a form of clustering in which each data point can belong to more than one cluster. Clustering or cluster analysis involves assigning data points to clusters (also called buckets, bins, or classes), or homogeneous classes, such that items in the same class or cluster are as similar as possible, while items … Read more
Feedforward Neural Network (FNN) is a biologically inspired classification algorithm. It consists of a (possibly large) number of simple neuron-like processing units, organized in layers. Every unit in a layer is connected with units in the previous layer. These connections are not all equal: each connection may have a different strength or weight. The weights on these connections encode the … Read more