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  2. Three-way comparison - Wikipedia

    en.wikipedia.org/wiki/Three-way_comparison

    In C++, the C++20 revision adds the spaceship operator <=>, which returns a value that encodes whether the 2 values are equal, less, greater, or unordered and can return different types depending on the strictness of the comparison. [3] The name's origin is due to it reminding Randal L. Schwartz of the spaceship in an HP BASIC Star Trek game. [4]

  3. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a user to act as though the index is an array-like sequence of integers, regardless of how it's actually defined. [9]: 110–113 Pandas supports hierarchical indices with multiple values per data point.

  4. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.

  5. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Since the range of values of raw data varies widely, in some machine learning algorithms, objective functions will not work properly without normalization. For example, many classifiers calculate the distance between two points by the Euclidean distance. If one of the features has a broad range of values, the distance will be governed by this ...

  6. Minkowski distance - Wikipedia

    en.wikipedia.org/wiki/Minkowski_distance

    However, a metric can be obtained for these values by simply removing the exponent of /. The resulting metric is also an F-norm . Minkowski distance is typically used with p {\displaystyle p} being 1 or 2, which correspond to the Manhattan distance and the Euclidean distance , respectively. [ 2 ]

  7. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    The original use of interpolation polynomials was to approximate values of important transcendental functions such as natural logarithm and trigonometric functions.Starting with a few accurately computed data points, the corresponding interpolation polynomial will approximate the function at an arbitrary nearby point.

  8. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    The Pandas and Polars Python libraries implement the Pearson correlation coefficient calculation as the default option for the methods pandas.DataFrame.corr and polars.corr, respectively. Wolfram Mathematica via the Correlation function, or (with the P value) with CorrelationTest. The Boost C++ library via the correlation_coefficient function.

  9. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A sigmoid function is a bounded, differentiable, real function that is defined for all real input values and has a non-negative derivative at each point [1] [2] and exactly one inflection point. Properties