Multispectral Image Analysis using Decision Trees
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 6
Abstract
Many machine learning algorithms have been used to classify pixels in Landsat imagery. The maximum likelihood classifier is the widely-accepted classifier. Non-parametric methods of classification include neural networks and decision trees. In this research work, we implemented decision trees using the C4.5 algorithm to classify pixels of a scene from Juneau, Alaska area obtained with Landsat 8, Operation Land Imager (OLI). One of the concerns with decision trees is that they are often over fitted with training set data, which yields less accuracy in classifying unknown data. To study the effect of overfitting, we have considered noisy training set data and built decision trees using randomly-selected training samples with variable sample sizes. One of the ways to overcome the overfitting problem is pruning a decision tree. We have generated pruned trees with data sets of various sizes and compared the accuracy obtained with pruned trees to the accuracy obtained with full decision trees. Furthermore, we extracted knowledge regarding classification rules from the pruned tree. To validate the rules, we built a fuzzy inference system (FIS) and reclassified the dataset. In designing the FIS, we used threshold values obtained from extracted rules to define input membership functions and used the extracted rules as the rule-base. The classification results obtained from decision trees and the FIS are evaluated using the overall accuracy obtained from the confusion matrix.
Authors and Affiliations
Arun Kulkarni, Anmol Shrestha
Optimization based Approach for Content Distribution in Hybrid Mobile Social Networks
This paper presents the new strategy for smooth content distribution in the mobile social network. We proposed a new method, hybrid mobile social network architecture scheme considered as one node of a social community c...
A High-Performing Similarity Measure for Categorical Dataset with SF-Tree Clustering Algorithm
Tasks such as clustering and classification assume the existence of a similarity measure to assess the similarity (or dissimilarity) of a pair of observations or clusters. The key difference between most clustering metho...
A Study on Sentiment Analysis Techniques of Twitter Data
The entire world is transforming quickly under the present innovations. The Internet has become a basic requirement for everybody with the Web being utilized in every field. With the rapid increase in social network appl...
Multi-Biometric Systems: A State of the Art Survey and Research Directions
Multi-biometrics is an exciting and interesting research topic. It is used to recognizing individuals for security purposes; to increase security levels. The recent research trends toward next biometrics generation in re...
Research on Chinese University Students’ Media Images
At present, university students, as the "after 90" and a new generation of young intellectuals, are being paid generally attentions by mass media. Nevertheless, university students’ public images are on a decline as they...