Nowadays it is of great importance for companies to make predictions, as well as to measure how they have behaved over time, in order to be able to plan the course of their business, reduce losses and increase profits. In order to generate an estimate of sales, different data mining techniques were analyzed. Among the techniques that were selected are time series, and within it, moving averages, exponential smoothing and trend adjusted exponential smoothing; linear regression and random trees were also selected. Prediction models were created with each one of the techniques, applying the corresponding equations and the information extracted from the database, in order to generate sales predictions with greater precision, to later compare the different results and measure the percentage of error.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nowadays it is of great importance for companies to make predictions, as well as to measure how they have behaved over time, in order to be able to plan the course of their business, reduce losses and increase profits. In order to generate an estimate of sales, different data mining techniques were analyzed. Among the techniques that were selected are time series, and within it, moving averages, exponential smoothing and trend adjusted exponential smoothing; linear regression and random trees were also selected. Prediction models were created with each one of the techniques, applying the corresponding equations and the information extracted from the database, in order to generate sales predictions with greater precision, to later compare the different results and measure the percentage of error. 88 pp. Englisch. Codice articolo 9786202722193
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Da: moluna, Greven, Germania
Condizione: New. Codice articolo 494130849
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. Neuware -Nowadays it is of great importance for companies to make predictions, as well as to measure how they have behaved over time, in order to be able to plan the course of their business, reduce losses and increase profits. In order to generate an estimate of sales, different data mining techniques were analyzed. Among the techniques that were selected are time series, and within it, moving averages, exponential smoothing and trend adjusted exponential smoothing; linear regression and random trees were also selected. Prediction models were created with each one of the techniques, applying the corresponding equations and the information extracted from the database, in order to generate sales predictions with greater precision, to later compare the different results and measure the percentage of error.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Codice articolo 9786202722193
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nowadays it is of great importance for companies to make predictions, as well as to measure how they have behaved over time, in order to be able to plan the course of their business, reduce losses and increase profits. In order to generate an estimate of sales, different data mining techniques were analyzed. Among the techniques that were selected are time series, and within it, moving averages, exponential smoothing and trend adjusted exponential smoothing; linear regression and random trees were also selected. Prediction models were created with each one of the techniques, applying the corresponding equations and the information extracted from the database, in order to generate sales predictions with greater precision, to later compare the different results and measure the percentage of error. Codice articolo 9786202722193
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Data prediction analysis with data mining techniques | Behaviour of different techniques | Teresita Moreno Ramírez (u. a.) | Taschenbuch | Englisch | 2020 | Our Knowledge Publishing | EAN 9786202722193 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 120439962
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