ISBN: 9786131696688 - concept drift: predictive analytics, machine learning, fraud, data stream mining, data mining, advertising, binary numeral system (4 risultati)

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Quality Content by WIKIPEDIA articles! In predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as the times passes. The term concept refers to the quantity you are looking to predict. More generally, it can also refer to other phenomena of interest besides the target concept, such as an input, but, in the context of concept drift, the term commonly refers to the target variable. The behavior of the customers in an online shop may change over time. Let's say you want to predict weekly merchandise sales, and you have developed a predictive model that works to your satisfaction. The model may use inputs such as the amount of money spent on advertising, promotions you are running, and other metrics that may affect sales. 96 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In predictive analytics and machine learning, the concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as the times passes. The term concept refers to the quantity you are looking to predict. More generally, it can also refer to other phenomena of interest besides the target concept, such as an input, but, in the context of concept drift, the term commonly refers to the target variable. The behavior of the customers in an online shop may change over time. Let's say you want to predict weekly merchandise sales, and you have developed a predictive model that works to your satisfaction. The model may use inputs such as the amount of money spent on advertising, promotions you are running, and other metrics that may affect sales.…

Taschenbuch. Condizione: Neu. Concept drift | Predictive analytics, Machine learning, Fraud, Data stream mining, Data mining, Advertising, Binary numeral system | Frederic P. Miller (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131696688 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In predictiveanalytics and machine learning, the concept drift means that thestatistical properties of the target variable, which the model is tryingto predict, change over time in unforeseen ways. This causes problemsbecause the predictions become less accurate as the times passes. Theterm concept refers to the quantity you are looking to predict. Moregenerally, it can also refer to other phenomena of interest besides thetarget concept, such as an input, but, in the context of concept driftthe term commonly refers to the target variable. The behavior of thecustomers in an online shop may change over time. Let's say you want topredict weekly merchandise sales, and you have developed a predictivemodel that works to your satisfaction. The model may use inputs such asthe amount of money spent on advertising, promotions you are runningand other metrics that may affect sales.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.…