Preparing the Features Dataset using Amibroker Exploration - Machine Learning

There are various methods to prepare the feature dataset, which is a crucial input for a machine learning prediction model. One approach is to code technical indicators using Python and feed them as input to the model. Another simpler approach is to utilize Amibroker's AFL Exploration, which provides built-in indicators and also supports custom indicators that are easy to code, explore, and prepare as feature datasets. The exploration dataset can then be extracted in CSV format. In machine learning, features represent the input data points or independent variables used to describe various aspects of the object under study.