Data Preparation
Time-series Data Preparation
Time-series Data Preparation organizes and formats transactional data into time-series data to predict trends and seasonality in the data. Transactional data is timestamped data recorded over a period at no specific frequency, while time-series data ...
Train Test Split in Forecasting
Train Test Split in Forecasting Description The data is split randomly into train data and test data. Ideally, the split is in the ratio of 70:30 or 80:20 for Train and test. Why to use To evaluate the accuracy of the model with an unknown dataset. ...
Lag
Lag Description Lag, also called the sliding window method, is a backshift operator function. The window width is the number of places the data points are shifted. Why to use Lag is used to create a new list of data points by shifting them by an ...
Time-series Data Preparation Tests in Forecasting
The different tests available in Time-series Data Preparation under Forecasting are given below. Accumulation Missing Value Transformation Differencing Data Preparation Description The time-series data may contain missing values that need to be ...
Data Preparation in Forecasting
Data Preparation is the process of cleaning and transforming raw data into organized data so that it can be processed and analyzed further. In data preparation, data is reformatted, corrected, and combined to enrich the data. Data preparation is ...