Preprocessing of Low Response Data for Predictive Modeling IJTSRD
For training a model, the raw data have to go through various preprocessing phases like Cleaning, Missing Values Imputation, Dimension Variable reduction, and Sampling. These steps are data and problem specific and affect the accuracy of the model at a very large extent. For the current scenario, we have 2.2M records with 511 variables. This […]