In this post I describe the important tasks of data preparation, exploration and binning.These three steps enable you to know your data well and build accurate predictive models. First you need to clean your data. Cleaning includes eliminating variables which have uneven spread across the target variable. I give an
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3 steps to prepare your data for accurate predictive models in SAS Enterprise Miner
Machine learning best practices: Autotune models to avoid local minimum breakdowns
This is the fifth post in my series of machine learning best practices. Hyperparameters are the algorithm options one "turns and tunes" when building a learning model. Hyperparameters cannot be learned using that algorithm. So, these parameters need to be assigned before training of the model. A lot of manual
Basic ODS Graphics: What is wrong with my SG annotation data set?
SG annotation is a powerful technique for adding text, lines, arrows, shapes, and images to graphs. This post provides a macro that can help you when you make a mistake in writing the annotations.