Mathematic

Sorites Paradox basically known as little-by-little arguments, which arise as a result of the indeterminacy surrounding limits of application of the predicates involved. Sorites Paradox…

Binary Classification algorithms is a prediction the score indicates the system’s certainty that the given observation belongs to the positive class. To make the decision…

Version Space Learning is, which itself is a set – possibly infinite – containing all consistent hypotheses, can be represented by just its lower and…

Supervised Learning is the machine learning, which is to build a model that makes predictions based on evidence in the presence of uncertainty. As adaptive…

This article talks about Q-Learning, which learns the optimal policy even when actions are selected according to a more exploratory or even random policy. It…

Temporal Difference Learning is an unsupervised technique in which the learning agent learns to predict the expected value of a variable occurring at the end…

This article talks about Support Vector Machine (SVM), which  is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training…

Analogical Modeling (AM) is an exemplar-based general theory of description that uses both neighbors and non-neighbors to predict language behavior. Analogical modeling is an appropriate…

Learning Vector Quantization (LVQ) has been studied to generate optimal reference vectors because of its simple and fast learning algorithm. It can be understood as…

Learning Automata is inconvenient to describe algorithms as finite-state automata, so a move was made to describe the internal state of the agent as a…

Group Method of Data Handling (GMDH) is a set of several algorithms for different problems solution. It consists of parametric, clusterization, analogues complexing, rebinarization and…

Mereotopology is today regarded as a major tool for formal-ontological analysis, and for many good reasons. It is highly general and highly domain independent. It…