Forecasting Costa Rican inflation with machine learning methods

Drought forecasting using new machine learning methods

In order to have effective agricultural production the impacts of drought must be mitigated. An important aspect of mitigating the impacts of drought is an effective method of forecasting future drought events. In this study, three methods of forecasting short-term drought for short lead times are explored in the Awash River Basin of Ethiopia. The Standardized Precipitation Index (SPI) was the ...

Forecasting terminal call rate with machine learning methods

This paper deals with the development of a model to predict the products’ terminal call rate (TCR) during the warranty period. TCR represents a key information for a quality management department to reserve the necessary funds for product repair during the warranty period. TCR prediction is often carried out by parametric models such as Poisson processes, ARIMA models and maximum likelihood est...

Costa Rican Natural History

Forecasting the Tehran Stock market by Machine ‎Learning Methods using a New Loss Function

Stock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is ...

Mining the Costa Rican Web

There is much to say about the structure and composition of a local web. Identification of authorities, topics and web communities can be used to improve search engines, change a portal design or to develop marketing strategies. The Costa Rican web was chosen as a test case for web mining analysis. After the study we obtained several descriptors of the web as well as the answers to typical ques...