Computers can be more verbose when it comes to finding patterns in the data under analysis. The aim is to create a system that needs only to be told where the data is, and how to find it, and that's it. It finds the patterns, and tells us, which patterns are interesting, so that we can sift through it for further analysis.
To research such a system and develop it, we make use of the colombia challenge dataset. This dataset is a dataset that has articles classified based on gender. Using this, we attempt to find if the system can start predicting the article's nature, before reading the next record. This is a classical attempt at reinforcement based learning.
Auto Pattern Finder automates the process that we keep on iterating our thoughts on. Using a multitude of algorithms that we make use, for evaluating objects, we can make the computer do the thinking for us. This is the basis for making this program.