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KNIME Prediction
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Classroom Contents
Time Series Analysis with the KNIME Analytics Platform - Preprocessing, Alignment, Imputation
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- 1 Introduction
- 2 Introductions
- 3 Agenda
- 4 What is Time Series Analysis
- 5 Time Series Data
- 6 Forecasting
- 7 Preprocessing
- 8 Time aggregation
- 9 Trend cycle
- 10 Seasonality
- 11 Modeling
- 12 KNIME Prediction
- 13 Other Considerations
- 14 Motivation
- 15 Arima Model
- 16 Autocorrelation Partial Autocorrelation
- 17 Model Identification
- 18 Seasonal Arena
- 19 Seasonal lags
- 20 Recap
- 21 Stream Learner
- 22 Time Series Components
