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Web frameworks can often be configured to model bind properties on view models that are strongly typed identifiers. Object–relational mappers can often be configured with value converters to map data between the properties on a model using strongly typed identifier data types and database columns.
Predicted fields are those whose values are predicted by the model. Outlier Treatment (attribute outliers): defines the outlier treatment to be use. In PMML, outliers can be treated as missing values, as extreme values (based on the definition of high and low values for a particular field), or as is.
In Object Pascal, all classes descend from the base TObject class, which implements basic RTTI functionality. Every class's name can be referenced in code for RTTI purposes; the class name identifier is implemented as a pointer to the class's metadata, which can be declared and used as a variable of type TClass.
FuelPHP, ORM and framework for PHP, released under the MIT license. Based on the ActiveRecord pattern. Laminas, framework that includes a table data gateway and row data gateway implementations; Qcodo, ORM and framework, open source; Redbean, ORM layer for PHP, for creating and maintaining tables on the fly, open source, BSD
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...
The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...
Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimizers, and a host of tools for working with image and text data to simplify programming in deep neural network area. [11]
A two-layer neural network capable of calculating XOR. The numbers within the neurons represent each neuron's explicit threshold. The numbers that annotate arrows represent the weight of the inputs. Note that If the threshold of 2 is met then a value of 1 is used for the weight multiplication to the next layer.