Hands-On Machine Learning on Google Cloud Platform

Data splitting

Let's now split the data for the training and the test model. Training and testing the model forms the basis for further usage of the model for prediction in predictive analytics. Given a dataset of 192 rows of data, we split it into a convenient ratio (say 70:30), and allocate 134 rows for training and 58 rows for testing.

In general, in the algorithms based on artificial neural networks, the splitting is done by selecting rows randomly to reduce the bias. With the time series data, the sequence of values is important, so this procedure is not practicable. A simple method that we can use is to divide the ordered dataset into train and test. As we anticipated, the following code calculates the division point index and separates ...