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A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
For example, Cem Kaner, James Bach, and Brett Pettichord explain in Lessons Learned in Software Testing: "The phrase smoke test comes from electronic hardware testing. You plug in a new board and turn on the power. If you see smoke coming from the board, turn off the power. You don't have to do any more testing." [3]
Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when run in PyPy. PyPy itself is built using a technique known as meta-tracing, which is a mostly automatic transformation that takes an interpreter as input and produces a tracing just-in-time compiler as ...
A sanity check or sanity test is a basic test to quickly evaluate whether a claim or the result of a calculation can possibly be true. It is a simple check to see if the produced material is rational (that the material's creator was thinking rationally, applying sanity ).
It is a common pattern in software testing to send values through test functions and check for correct output. In many cases, in order to thoroughly test functionalities, one needs to test multiple sets of input/output, and writing such cases separately would cause duplicate code as most of the actions would remain the same, only differing in input/output values.
The science of silent snowflakes: The most common type of snowflake, called a dendrite, has six "arms" extending out from the center of the flake. While falling toward the ground, these dendrites ...
Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]
Python: Application, general, web, scripting, artificial intelligence, scientific computing Yes Yes Yes Yes Yes Yes Aspect-oriented De facto standard via Python Enhancement Proposals (PEPs) R: Application, statistics Yes Yes Yes Yes No Yes No Racket: Education, general, scripting Yes Yes Yes Yes No Yes Modular, logic, meta No Raku