Winson Digital Techniques

Data Splitting What is data splitting? Data splitting is when data is divided into two or more subsets. Typically, with a two-part split, one part is used to evaluate or test the data and the other to train the model. Data splitting is an important aspect of data science, particularly for creating models based on data. This technique helps ensure the creation of data models and processes that use data models -- such as machine learning  -- are accurate. How data splitting works In a basic two-part data split, the training data set is used to train and develop models. Training sets are commonly used to estimate different parameters or to compare different model performances. The  testing data set is used after the training is done. The training and test data are compared to check that the final model works correctly. With machine learning, data is commonly split into three or more sets. With three sets, the additional set is the dev set, which is used to change learni...