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  2. Dataframe - Wikipedia

    en.wikipedia.org/wiki/Dataframe

    Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;

  3. NaN - Wikipedia

    en.wikipedia.org/wiki/NaN

    Using a limited amount of NaN representations allows the system to use other possible NaN values for non-arithmetic purposes, the most important being "NaN-boxing", i.e. using the payload for arbitrary data. [23] (This concept of "canonical NaN" is not the same as the concept of a "canonical encoding" in IEEE 754.)

  4. Missing data - Wikipedia

    en.wikipedia.org/wiki/Missing_data

    The presence of structured missingness may be a hindrance to make effective use of data at scale, including through both classical statistical and current machine learning methods. For example, there might be bias inherent in the reasons why some data might be missing in patterns, which might have implications in predictive fairness for machine ...

  5. t-distributed stochastic neighbor embedding - Wikipedia

    en.wikipedia.org/wiki/T-distributed_stochastic...

    The bandwidth of the Gaussian kernels is set in such a way that the entropy of the conditional distribution equals a predefined entropy using the bisection method. As a result, the bandwidth is adapted to the density of the data: smaller values of σ i {\displaystyle \sigma _{i}} are used in denser parts of the data space.

  6. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    The effect of z-score normalization on k-means clustering. 4 gaussian clusters of points are generated, then squashed along the y-axis, and a = clustering was computed. . Without normalization, the clusters were arranged along the x-axis, since it is the axis with most of varia

  7. Exponential smoothing - Wikipedia

    en.wikipedia.org/wiki/Exponential_smoothing

    Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned ...

  8. Why You Should Never Try to Out-Run a Grizzly Bear - AOL

    www.aol.com/why-never-try-run-grizzly-174419138.html

    Watch the Video. Click here to watch on YouTube. Biking can be a fun way to pass the time and get some exercise in the great outdoors. However, depending on your chosen trail, a joyful ride can ...

  9. Assertion (software development) - Wikipedia

    en.wikipedia.org/wiki/Assertion_(software...

    In computer programming, specifically when using the imperative programming paradigm, an assertion is a predicate (a Boolean-valued function over the state space, usually expressed as a logical proposition using the variables of a program) connected to a point in the program, that always should evaluate to true at that point in code execution.