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Connect for Forecasting and Predictive Analytics
7th Edición
1260165485
·
9781260165487
© 2019 | Published: April 26, 2018
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Chapter 1: Introduction to Business Forecasting and Predictive Analytics
Chapter 2:The Forecast Process, Data Considerations, and Model Selection
Chapter 3:Extrapolation 1. Moving Averages and Exponential Smoothing
Chapter 4:Extrapolation 2. Introduction to Forecasting with Regression Trend Models
Chapter 5:Explanatory Models 1. Forecasting with Multiple Regression Causal Models
Chapter 6:Explanatory Models 2. Time-Series Decomposition
Chapter 7:Explanatory Models 3. ARIMA (Box-Jenkins) Forecasting Models
Chapter 8:Predictive Analytics: Helping to Make Sense of Big Data
Chapter 9:Classification Models: The Most Used Models in Analytics
Chapter 10:Ensemble Models and Clustering
Chapter 11:Text Mining
Chapter 12:Forecast/Analytics Implementation
Chapter 2:The Forecast Process, Data Considerations, and Model Selection
Chapter 3:Extrapolation 1. Moving Averages and Exponential Smoothing
Chapter 4:Extrapolation 2. Introduction to Forecasting with Regression Trend Models
Chapter 5:Explanatory Models 1. Forecasting with Multiple Regression Causal Models
Chapter 6:Explanatory Models 2. Time-Series Decomposition
Chapter 7:Explanatory Models 3. ARIMA (Box-Jenkins) Forecasting Models
Chapter 8:Predictive Analytics: Helping to Make Sense of Big Data
Chapter 9:Classification Models: The Most Used Models in Analytics
Chapter 10:Ensemble Models and Clustering
Chapter 11:Text Mining
Chapter 12:Forecast/Analytics Implementation