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prediction of poverty, random forest is rarely used. Comparing out-of-sample predictions in surveys for same year in six … selected by stepwise and Lasso), suggesting that this method could contribute to better poverty predictions. However, none of … the methods consistently provides accurate predictions of poverty over time, highlighting that technical model fitting by …
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Insolvenzprognosen und Ratings sind wichtige Aufgaben der Finanzbranche und dienen der Kreditwürdigkeitsprüfung von Unternehmen. Eine Möglichkeit dieses Aufgabenfeld anzugehen, ist maschinelles Lernen. Dabei werden Vorhersagemodelle aufgrund von Beispieldaten aufgestellt. Methoden aus diesem...
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Across disciplines, researchers and practitioners employ decision tree ensembles such as random forests and XGBoost with great success. What explains their popularity? This chapter showcases how marketing scholars and decision makers can harness the power of decision tree ensembles for academic...
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Low visibility conditions enforce special procedures that reduce the operational flight capacity at airports. Accurate and probabilistic forecasts of these capacity-reducing lowvisibility procedure (lvp) states help the air traffic management to optimize flight planning and regulation. In this...
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Low-visibility conditions at airports can lead to capacity reductions and therefore to delays or cancelations of arriving and departing flights. Accurate visibility forecasts are required to keep the airport capacity as high as possible. We generate probabilistic nowcasts of low-visibility...
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