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(mathematics):
Intron (molecular
biology):
Isoelectric point
(chemistry):
Iterable (computing):
Iterate (computing):
Iterator (computing):
Java (computing):
A specification for the functionality provided by a class or
module, without worrying about how that functionality is
actually implemented.
The common elements between two collections, usually sets.
The non-coding parts in the middle of genes. Intron sequences
are initially transcribed into RNA, but are removed to make
mature RNA molecules, and so do not contribute to the final
product. Introns separate a gene’s exons, which do form the
mature RNA and thus may encode protein sequence.
The pH at which a molecule has no overall charge; naturally
only relevant for molecules that contain acidic and/or basic
chemical groups.
A property whereby an object can provide the individual
members from a group of items, e.g. from a list. In Python an
iterable object can be used to provide a sequence of items, such
as in a ‘for’ loop. This is a concept distinct from the iterator
object (see below), though all iterable objects can be converted
into iterators using the iter() function.
The process of repeating the same basic operation a number of
times, such as extracting all the items from a list in sequence. In
the context of algorithms this might be to improve the solution
to a problem, where the solution to one cycle serves as a
foundation for the next.
An object that emits a succession of items, by continually
asking for the ‘next’ item until all items have been considered.
In Python an iterator is a special kind of object that provides the
next item in a data sequence via its __next()__ method (in
Python 3; next() in Python 2). In this context an iterator is
distinct from an iterable, which does not support the __next()__
method but which can nonetheless be used in loops etc. All
iterators are iterable but not vice versa.
A compiled, object-oriented programming language commonly
used for database and internet applications.
Join (computing):
K
a
(chemistry):
K-dimensional trees
(computing):
Kernel methods
(computing):
Kernel trick
(mathematics):
Key, value (computing):
k-nearest neighbour
(computing):
Kohonen map
(computing):
Layout (graphics):
With regard to databases the way information can be linked
across different tables.
A symbolic abbreviation for the acid dissociation constant.
A way of grouping data with K dimensions (independent data
axes) into a tree-like structure, i.e. a hierarchy of branching
nodes. Such an arrangement can make particular operations,
such as finding data points within a given radius, more efficient.
The basic notion is that the tree arrangement means that only
some of the data needs to be checked.
A type of algorithm used for machine learning (pattern
recognition) where the original data are placed in a vector space
so that the data may be analysed in terms of the distance
between points. Such methods often use a kernel function to
efficiently calculate the coincidence or similarity (inner product)
between data points.
The means by which a kernel method uses a kernel function to
effectively map a pattern-recognition problem to one of higher
dimensionality, e.g. to help separate data into categories. This is
achieved by calculating inner products, as a measure of
coincidence in the data, and eliminates the need to explicitly
represent the data in the higher dimensions.
The pairs of items that constitute a dictionary data structure. The
key is a unique, unmodifiable item that is used to access the
corresponding value.
A simple machine learning algorithm that classifies data by
finding the k nearest neighbours in the feature space,
representing the closest data points with known classification.
The classification is assigned by taking a poll of the classes
represented in the neighbouring points.
A synonym for a self-organising map (see below), named after
Teuvo Kohonen.
With reference to graphical user interfaces, the relative
Likelihood ratio test
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