Embankment damAn embankment dam is a large artificial dam. It is typically created by the placement and compaction of a complex semi-plastic mound of various compositions of soil or rock. It has a semi-pervious waterproof natural covering for its surface and a dense, impervious core. This makes the dam impervious to surface or seepage erosion. Such a dam is composed of fragmented independent material particles. The friction and interaction of particles binds the particles together into a stable mass rather than by the use of a cementing substance.
Residual sum of squaresIn statistics, the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation model, such as a linear regression. A small RSS indicates a tight fit of the model to the data. It is used as an optimality criterion in parameter selection and model selection.
Design matrixIn statistics and in particular in regression analysis, a design matrix, also known as model matrix or regressor matrix and often denoted by X, is a matrix of values of explanatory variables of a set of objects. Each row represents an individual object, with the successive columns corresponding to the variables and their specific values for that object. The design matrix is used in certain statistical models, e.g., the general linear model.
Aswan DamThe Aswan Dam, or more specifically since the 1980s, the Aswan High Dam, is one of the world's largest embankment dams, which was built across the Nile in Aswan, Egypt, between 1960 and 1970. Its significance largely eclipsed the previous Aswan Low Dam initially completed in 1902 downstream. Based on the success of the Low Dam, then at its maximum utilization, construction of the High Dam became a key objective of the government following the Egyptian Revolution of 1952; with its ability to better control flooding, provide increased water storage for irrigation and generate hydroelectricity, the dam was seen as pivotal to Egypt's planned industrialization.
Tucuruí DamThe Tucuruí Dam (Tucuruí means "grasshopper's water", translated from Tupí language; Tucuruí) is a concrete gravity dam on the Tocantins River located on the Tucuruí County in the State of Pará, Brazil. The main purpose of the dam is hydroelectric power production and navigation. It is the first large-scale hydroelectric project in the Brazilian Amazon rainforest. The installed capacity of the 25-unit plant is . Phase I construction began in 1980 and ended in 1984 while Phase II began in 1998 and ended in 2010.
Shrinkage (statistics)In statistics, shrinkage is the reduction in the effects of sampling variation. In regression analysis, a fitted relationship appears to perform less well on a new data set than on the data set used for fitting. In particular the value of the coefficient of determination 'shrinks'. This idea is complementary to overfitting and, separately, to the standard adjustment made in the coefficient of determination to compensate for the subjunctive effects of further sampling, like controlling for the potential of new explanatory terms improving the model by chance: that is, the adjustment formula itself provides "shrinkage.
Phi coefficientIn statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or rφ) is a measure of association for two binary variables. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975. Introduced by Karl Pearson, and also known as the Yule phi coefficient from its introduction by Udny Yule in 1912 this measure is similar to the Pearson correlation coefficient in its interpretation.
Evaluation of binary classifiersThe evaluation of binary classifiers compares two methods of assigning a binary attribute, one of which is usually a standard method and the other is being investigated. There are many metrics that can be used to measure the performance of a classifier or predictor; different fields have different preferences for specific metrics due to different goals. For example, in medicine sensitivity and specificity are often used, while in computer science precision and recall are preferred.
