Testing Machine Learning Algorithms with K-Fold Cross Validation - Talend

In an earlier post on Applying Machine Learning to IoT Sensors, I discussed the process for classifying sensor data with a machine learning algorithm. In this post, I'll give a background on choosing an algorithm, then using a validation technique. For the technique, I'll show how to apply it, and how it can be built using the Talend Studio without hand coding. Given a prediction scenario involving a machine learning algorithm, the first question to ask is what is the appropriate machine learning algorithm? Taking the example of predicting a user's activity based on mobile phone accelerometer data, we must be able to classify a category for the data (resting, walking, or running).