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  2. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Time series models are a subset of machine learning that utilize time series in order to understand and forecast data using past values. A time series is the sequence of a variable's value over equally spaced periods, such as years or quarters in business applications. [11]

  3. Unevenly spaced time series - Wikipedia

    en.wikipedia.org/wiki/Unevenly_spaced_time_series

    Traces is a Python library for analysis of unevenly spaced time series in their unaltered form.; CRAN Task View: Time Series Analysis is a list describing many R (programming language) packages dealing with both unevenly (or irregularly) and evenly spaced time series and many related aspects, including uncertainty.

  4. Mixed-data sampling - Wikipedia

    en.wikipedia.org/wiki/Mixed-data_sampling

    The MIDAS can also be used for machine learning time series and panel data nowcasting. [6] [7] The machine learning MIDAS regressions involve Legendre polynomials.High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.

  5. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. Generally, time series data is modelled as a stochastic process.

  6. 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 ...

  7. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    This data is not pre-processed List of GitHub repositories of the project: Red Hat partner This data is not pre-processed List of GitHub repositories of the project: IBM Repositories This data is not pre-processed List of GitHub repositories for the project: Build Lab Team This data is not pre-processed List of GitHub repositories for the project

  8. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data; PSPP – A free software alternative to IBM SPSS Statistics

  9. Bayesian structural time series - Wikipedia

    en.wikipedia.org/.../Bayesian_structural_time_series

    Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The model has also promising application in the field of analytical marketing. In particular, it can be used ...