Search results
Results From The WOW.Com Content Network
Brian is aimed at researchers developing models based on networks of spiking neurons. The general design is aimed at maximising flexibility, simplicity and users' development time. [ 2 ] Users specify neuron models by giving their differential equations in standard mathematical form as strings , create groups of neurons and connect them via ...
The MIDAS can also be used for machine learning time series and panel data nowcasting. [6] [7] The machine learning MIDAS regressions involve Legendre polynomials.High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.
In object-oriented programming, the singleton pattern is software design pattern that restricts the instantiation of a class to a singular instance. It is one of the well-known "Gang of Four" design patterns , which describe how to solve recurring problems in object-oriented software. [ 1 ]
For example, a generic data model may define relation types such as a 'classification relation', being a binary relation between an individual thing and a kind of thing (a class) and a 'part-whole relation', being a binary relation between two things, one with the role of part, the other with the role of whole, regardless the kind of things ...
The Visitor Family of Design Patterns at the Wayback Machine (archived October 22, 2015). Additional archives: April 12, 2004, March 5, 2002. A rough chapter from The Principles, Patterns, and Practices of Agile Software Development, Robert C. Martin, Prentice Hall; Visitor pattern in UML and in LePUS3 (a Design Description Language)
A further related development is factor-based PLS-PM (PLSF), a variation of which employs PLSc-PM as a basis for the estimation of the factors in common factor models; this method significantly increases the number of common factor model parameters that can be estimated, effectively bridging the gap between classic PLS-PM and covariance‐based ...
Initial sample selection (the experiments and/or simulations to be run) Construct surrogate model; Search surrogate model (the model can be searched extensively, e.g., using a genetic algorithm, as it is cheap to evaluate) Run and update experiment/simulation at new location(s) found by search and add to sample
Gensim is implemented in Python and Cython for performance. Gensim is designed to handle large text collections using data streaming and incremental online algorithms, which differentiates it from most other machine learning software packages that target only in-memory processing.