Category Archives: Data Processing
Missing data imputation for deep learning tasks
Let’s say you have a dataset with missing values that you want to use to train a deep neural network. You can use the following approach to handle the missing values: Here is some sample code that demonstrates how to handle missing values in a deep neural network using this approach:
Missing values and supervised learning
Missing values in supervised learning can be a major issue, as they can reduce the accuracy of the model and lead to poor performance. Several approaches can be taken to address missing values in supervised learning, including: Ultimately, the best approach to dealing with missing values in supervised learning will depend on the dataset’s specific…