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    Tables – Mathematics – Probability Algorithms

    Probability AlgorithmDescription
    Bayes’ TheoremUses prior knowledge to calculate the probability of an event given new evidence
    Markov ChainsA sequence of possible events, where the probability of each event depends only on the state attained in the previous event
    Monte Carlo SimulationUses repeated random sampling to estimate statistical properties of some phenomenon
    Poisson ProcessModels the number of times certain events occur within a specified interval of time or space
    Naive Bayes ClassifierAssumes independent predictors and calculates the probability of a class based on the presence of various predictors
    Maximum Likelihood EstimationEstimates the parameters of a statistical model by maximising the likelihood function
    Gaussian Mixture ModelsRepresents a composite distribution whereby points are drawn from one of several Gaussian sub-distributions, each specified by their mean and covariance
    Bernoulli ProcessSpecial type of a Poisson process where the time between two events follows an exponential distribution
    Expectation-MaximizationAn iterative method to find maximum likelihood or maximum a posteriori estimates of parameters in statistical models
    Hidden Markov ModelAssumes the Markov property to model hidden states
    Machine Learning Algorithms using ProbabilityThey apply probability and statistical concepts to predict the outcome
    Bayesian NetworksRepresents a set of variables and their conditional dependencies via a directed acyclic graph
    Conditional Random FieldsUsed in machine learning to predict a sequence of states given a sequence of observations
    Logistic RegressionEstimates parameters of a logistic model and thereby predicting the probability of occurrence of an event
    Normal DistributionA probability function that describes how the values of a variable are distributed
    Kernel Density EstimationA non-parametric way of estimating the probability density function of a random variable
    Chi Square TestAssess two types of comparison: tests of independence and goodness of fit
    Fisher’s exact testFinds statistical significance in a 2×2 contingency table
    Information Gain & EntropyDetermine the best attribute for ID3 decision tree algorithm
    Student’s T-testEstimates whether the means of two groups are statistically different from each other