Artículos académicos Profitability prediction in catlle ranches in Latin America: A Machine Learning Approach

Profitability prediction in catlle ranches in Latin America: A Machine Learning Approach

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Autoría

Año de publicación

2014

Palabras clave

Rentabilidad, Aprendizaje automático, Ganadería, VSM, KRR

Título en español

Predicción de Rentabilidad en Ganaderías de América Latina: Un Enfoque de Aprendizaje Automático

Descripción

As the cattle ranchin Latin America transformsitself from a macho activity to a normal business, the application of information technology and business principles becomes increasingly important. At the same time, on account of globalisation and technological developments more and more ranches have absentee owners and professional managers who have started using better data processing techniques. A mathematical model to aid in predicting the profitability of ranch operations would be of immense use to the managers. It may be used as the primary source of predicting profitability whilst some managers may use it as a valuable second opinion. Furthermore, it would of considerable interest to commercial managers to know the effect on predicted profitability should they change the value of an attribute of a activity. The paper demonstrates that both the Vector Space Model and Kernel Ridge Regression routines are fairly simple to implement in a commercial setting. Commercial application will, however, require close interaction between veterinary scientists and business scholars. (Asthana, A. N., 2014)

Referencia

Asthana, A. N. (2014). Profitability prediction in catlle ranches in Latin America: A Machine Learning Approach. Global Veterinaria, 13(4), 473-495. doi:10.5829/idosi.gv.2014.13.04.1179

Anand Narain Asthana

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