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  2. Makridakis Competitions - Wikipedia

    en.wikipedia.org/wiki/Makridakis_Competitions

    The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy of different time series forecasting methods. They are organized by teams led by forecasting researcher Spyros Makridakis and were first held in 1982. [1] [2] [3] [4]

  3. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  4. Global Energy Forecasting Competition - Wikipedia

    en.wikipedia.org/wiki/Global_Energy_Forecasting...

    It included two tracks: a hierarchical load forecasting track and a wind power forecasting track; both opened to contestants in September 2012. [9] [10] More than 200 teams submitted more than 2,000 entries focusing on hierarchical load forecasting and wind power forecasting. The winners were announced by the IEEE Power & Energy Society (one of ...

  5. Model output statistics - Wikipedia

    en.wikipedia.org/wiki/Model_output_statistics

    In weather forecasting, model output statistics (MOS) is a multiple linear regression technique in which predictands, often near-surface quantities (such as two-meter-above-ground-level air temperature, horizontal visibility, and wind direction, speed and gusts), are related statistically to one or more predictors.

  6. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...

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

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

    Nomao collects data about places from many different sources. Task is to detect items that describe the same place. Duplicates labeled. 34,465 Text Classification 2012 [487] [488] Nomao Labs Movie Dataset Data for 10,000 movies. Several features for each movie are given. 10,000 Text Clustering, classification 1999 [489] G. Wiederhold

  8. Forecast either to existing data (static forecast) or "ahead" (dynamic forecast, forward in time) with these ARMA terms. Apply the reverse filter operation (fractional integration to the same level d as in step 1) to the forecasted series, to return the forecast to the original problem units (e.g. turn the ersatz units back into Price).

  9. Marketing mix modeling - Wikipedia

    en.wikipedia.org/wiki/Marketing_mix_modeling

    Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.

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