Search results
Results From The WOW.Com Content Network
Synthetic-aperture sonar (SAS) is a form of sonar in which sophisticated post-processing of sonar data is used in ways closely analogous to synthetic-aperture radar. Synthetic-aperture sonars combine a number of acoustic pings to form an image with much higher along-track resolution than conventional sonars.
The SAS macro language is made available within base SAS software to reduce the amount of code, and create code generators for building more versatile and flexible programs. [21] The macro language can be used for functionalities as simple as symbolic substitution and as complex as dynamic programming . [ 8 ]
SAS/GRAPH, which produces graphics, was released in 1980, as well as the SAS/ETS component, which supports econometric and time series analysis. A component intended for pharmaceutical users, SAS/PH-Clinical, was released in the 1990s. The Food and Drug Administration standardized on using SAS/PH-Clinical for new drug applications in 2002. [20]
RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [90] [91] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
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]
SAS Institute (or SAS, pronounced "sass") is an American multinational developer of analytics and artificial intelligence software based in Cary, North Carolina. SAS develops and markets a suite of analytics software ( also called SAS ), which helps access, manage, analyze and report on data to aid in decision-making.
It was proven in 2014 that the elastic net can be reduced to the linear support vector machine. [7] A similar reduction was previously proven for the LASSO in 2014. [8] The authors showed that for every instance of the elastic net, an artificial binary classification problem can be constructed such that the hyper-plane solution of a linear support vector machine (SVM) is identical to the ...
The main approaches for stepwise regression are: Forward selection, which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically significant improvement of the fit, and repeating this process until none improves the model to a statistically significant ...