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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]
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.
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.
A financial forecast is an estimate of future financial outcomes for a company or project, usually applied in budgeting, capital budgeting and / or valuation. Depending on context, the term may also refer to listed company (quarterly) earnings guidance. For a country or economy, see Economic forecast.
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.
ESG corpus: Knowledge Hub of the Accounting for Sustainability This data is not pre-processed Guides, case studies, blogs, and reports & surveys. [391] Mehra et al. CLIMATE-FEVER A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet.
In project management, trend analysis is a mathematical technique that uses historical results to predict future outcome. This is achieved by tracking variances in cost and schedule performance. In this context, it is a project management quality control tool. [4] [5]
Reference class forecasting or comparison class forecasting is a method of predicting the future by looking at similar past situations and their outcomes. The theories behind reference class forecasting were developed by Daniel Kahneman and Amos Tversky. The theoretical work helped Kahneman win the Nobel Prize in Economics.