36. Learning is
The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system
It automatically maps an external signal space into a system's internal representational space. They are useful in the performance of classification tasks.
A process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out.
None of these
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37. Naive prediction is
A class of learning algorithms that try to derive a Prolog program from examples
A table with n independent attributes can be seen as an n-dimensional space.
A prediction made using an extremely simple method, such as always predicting the same output
38. Learning algorithm referrers to
An algorithm that can learn
A sub-discipline of computer science that deals with the design and implementation of learning algorithms
A machine-learning approach that abstracts from the actual strategy of an individual algorithm and can, therefore, be applied to any other form of machine learning.
39. Knowledge is referred to
Non-trivial extraction of implicit previously unknown and potentially useful information from data
Set of columns in a database table that can be used to identify each record within this table uniquely
collection of interesting and useful patterns in a database
none of these
40. Node is
A component of a network
In the context of KDD and data mining, this refers to random errors in a database table.
One of the defining aspects of a data warehouse
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