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Data transformation (statistics) A scatterplot in which the areas of the sovereign states and dependent territories in the world are plotted on the vertical axis against their populations on the horizontal axis. The upper plot uses raw data. In the lower plot, both the area and population data have been transformed using the logarithm function.
Microsoft Excel A simple bar graph being created in Excel, running on Windows 11 Developer(s) Microsoft Initial release November 19, 1987 ; 36 years ago (1987-11-19) Stable release 2312 (Build 17126.20132) / January 9, 2024 ; 9 months ago (2024-01-09) Written in C++ (back-end) Operating system Microsoft Windows Type Spreadsheet License Trialware Website microsoft.com microsoft-365 /excel ...
t. e. In statistics, an expectation–maximization (EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. [ 1 ] The EM iteration alternates between performing an expectation (E) step, which ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates. [ 2 ][ 3 ] This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods. [ 1 ] Bootstrapping estimates the properties of an estimand (such as its variance) by ...
An explanation of logistic regression can begin with an explanation of the standard logistic function. The logistic function is a sigmoid function, which takes any real input , and outputs a value between zero and one. [2] For the logit, this is interpreted as taking input log-odds and having output probability.
Discrete logarithm. Appearance. In mathematics, for given real numbers a and b, the logarithm log b a is a number x such that bx = a. Analogously, in any group G, powers bk can be defined for all integers k, and the discrete logarithm log b a is an integer k such that bk = a.
In mathematics, the logarithmto basebis the inverse function of exponentiationwith base b. That means that the logarithm of a number xto the base bis the exponentto which bmust be raised to produce x. For example, since 1000 = 103, the logarithm base 10{\displaystyle 10}of 1000is 3, or log10 (1000) = 3.