Machine Learning

The following is not a full comprehension of my machine learning knowledge and experience, but rather a few select samples. Code for implementing several algorithms is found in the in the gridding link.

Clustering

• Used for grouping together elements based on attributes, like TSA could look at the attributes of a person, and try to label whether that person is a threat or not.

Algorithm Gridding

• Running one or many datasets through several algorithms in order to see which one would predict best each dataset.

Neural Network

• An algorithm that changes weights based on prediction error to best learn the attributes of a dataset, and therefore predict the best possible.

KNN Regression

• A regression method where values are predicted for each row of a dataset based on calculated proximity to training set rows.

Association Rule Mining

• Used for finding out which items are commonly grouped together, or leads to other items, which is very useful in analyzing shopping data.