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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]
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.
John Galt Solutions was founded in 1996 by Annemarie Omrod. [2] [3] [4] The company is named after the iconic figure in Ayn Rand's novel Atlas Shrugged, John Galt. [1] [2] John Galt Solutions' initial projects involved building data warehouses for utility companies. [1] [4] In 1997, John Galt Solutions built its forecasting tool the ForecastX ...
The Global Energy Forecasting Competition (GEFCom) is a competition conducted by a team led by Dr. Tao Hong that invites submissions around the world for forecasting energy demand. [1] GEFCom was first held in 2012 on Kaggle , [ 2 ] and the second GEFCom was held in 2014 on CrowdANALYTIX.
A set of books extracted from the Project Gutenberg books library Text Natural Language Processing 2019 Jack W et al. Deepmind Mathematics: Mathematical question and answer pairs. Text Natural Language Processing 2018 [115] D Saxton et al. Anna's Archive: A comprehensive archive of published books and papers None 100,356,641 Text, epub, PDF
Activity-based costing was first clearly defined in 1987 by Robert S. Kaplan and W. Bruns as a chapter in their book Accounting and Management: A Field Study Perspective. They initially focused on the manufacturing industry, where increasing technology and productivity improvements have reduced the relative proportion of the direct costs of ...
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.
IBM SPSS: includes ARIMA modeling in the Professional and Premium editions of its Statistics package as well as its Modeler package. The default Expert Modeler feature evaluates a range of seasonal and non-seasonal autoregressive ( p ), integrated ( d ), and moving average ( q ) settings and seven exponential smoothing models.