Machine Learning Techniques for Better Data Driven Decisions Revisited

Abstract

The main goal of machine learning is to accurately predict the decisions to the problems without human expert intervention. These decisions depend upon patterns found and facts learnt during training tenure. However, prior incorporation of human knowledge is necessary for better prediction of the test data. The main aim is to make machines self-reliant for decision making. Providing machine with this vision makes it useful in every modern field. This makes the stepping stone to make computers behave as the humans do. Enhancing its speed and accuracy are the next step in this field. This paper presents a stock of techniques used to train the machines to respond to patterns present in the data sets so that useful information may be extracted for its potential use.