Supervised and Unsupervised Machine Learning Methodologies for Crime Pattern Analysis

Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification

This paper presents a comparative account of unsupervised and supervised learning models and their pattern classification evaluations as applied to the higher education scenario. Classification plays a vital role in machine based learning algorithms and in the present study, we found that, though the error back-propagation learning algorithm as provided by supervised learning model is very effi...

Novel strategies on semi-supervised and unsupervised machine learning

Unsupervised Change Analysis Using Supervised Learning

We propose a formulation of a new problem, which we call change analysis, and a novel method for solving the problem. In contrast to the existing methods of change (or outlier) detection, the goal of change analysis goes beyond detecting whether or not any changes exist. Its ultimate goal is to find the explanation of the changes. While change analysis falls in the category of unsupervised lear...

Supervised and Unsupervised Learning for Sentence Compression

In Statistics-Based Summarization Step One: Sentence Compression, Knight and Marcu (Knight and Marcu, 2000) (K&M) present a noisy-channel model for sentence compression. The main difficulty in using this method is the lack of data; Knight and Marcu use a corpus of 1035 training sentences. More data is not easily available, so in addition to improving the original K&M noisy-channel model, we cre...

Combining Unsupervised and Supervised Machine Learning to Build User Models for Intelligent Learning Environments

Traditional approaches to developing user models, especially for computer-based learning environments, are notoriously difficult and time-consuming because they rely heavily on expert-elicited knowledge about the target application and domain. Furthermore, because the necessary expert knowledge is application and domain specific, the entire model development process must be repeated for each ne...