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  2. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    Instance normalization (InstanceNorm), or contrast normalization, is a technique first developed for neural style transfer, and is also only used for CNNs. [26] It can be understood as the LayerNorm for CNN applied once per channel, or equivalently, as group normalization where each group consists of a single channel:

  3. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    In a neural network, batch normalization is achieved through a normalization step that fixes the means and variances of each layer's inputs. Ideally, the normalization would be conducted over the entire training set, but to use this step jointly with stochastic optimization methods, it is impractical to use the global information.

  4. Flyweight pattern - Wikipedia

    en.wikipedia.org/wiki/Flyweight_pattern

    In computer programming, the flyweight software design pattern refers to an object that minimizes memory usage by sharing some of its data with other similar objects. The flyweight pattern is one of twenty-three well-known GoF design patterns . [ 1 ]

  5. Shard (database architecture) - Wikipedia

    en.wikipedia.org/wiki/Shard_(database_architecture)

    Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...

  6. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  7. Normalisation by evaluation - Wikipedia

    en.wikipedia.org/wiki/Normalisation_by_evaluation

    In programming language semantics, normalisation by evaluation (NBE) is a method of obtaining the normal form of terms in the λ-calculus by appealing to their denotational semantics. A term is first interpreted into a denotational model of the λ-term structure, and then a canonical (β-normal and η-long) representative is extracted by ...

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Instances Format Default Task Created (updated) Reference Creator Geographic Origin of Music Data Set Audio features of music samples from different locations. Audio features extracted using MARSYAS software. 1,059 Text Geographic classification, clustering 2014 [138] [139] F. Zhou et al. Million Song Dataset

  9. Multiclass classification - Wikipedia

    en.wikipedia.org/wiki/Multiclass_classification

    Based on learning paradigms, the existing multi-class classification techniques can be classified into batch learning and online learning. Batch learning algorithms require all the data samples to be available beforehand. It trains the model using the entire training data and then predicts the test sample using the found relationship.

  1. Related searches instance normalization vs batch size in python programming software on website

    batch normalization wikibatch normalization ppt