Performance Analysis and Evaluation of Different Data Mining Algorithms used for Cancer Classification
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2013, Vol 2, Issue 5
Abstract
Classification algorithms of data mining have been successfully applied in the recent years to predict cancer based on the gene expression data. Micro-array is a powerful diagnostic tool that can generate handful information of gene expression of all the human genes in a cell at once. Various classification algorithms can be applied on such micro-array data to devise methods that can predict the occurrence of tumor. However, the accuracy of such methods differ according to the classification algorithm used. Identifying the best classification algorithm among all available is a challenging task. In this study, we have made a comprehensive comparative analysis of 14 different classification algorithms and their performance has been evaluated by using 3 different cancer data sets. The results indicate that none of the classifiers outperformed all others in terms of the accuracy when applied on all the 3 data sets. Most of the algorithms performed better as the size of the data set is increased. We recommend the users not to stick to a particular classification method and should evaluate different classification algorithms and select the better algorithm.
Authors and Affiliations
Gopala Krishna Nookala, Bharath Pottumuthu, Nagaraju Orsu, Suresh Mudunuri
Vital Sign and Location/Attitude Monitoring with Sensor Networks for the Proposed Rescue System for Disabled and Elderly Persons Who Need a Help in Evacuation from Disaster Areas
Method and system for vital sign (Body temperature, blood pressure, bless, Heart beat pulse rate, and consciousness) and location/attitude monitoring with sensor network for the proposed rescue system for disabled...
Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules
This research aims to calculate the execution time for software modules, using Particle Swarm Optimization (PSO) and Parallel Particle Swarm Optimization (PPSO), in order to calculate the proper time. A comparison...
A Rank Aggregation Algorithm for Ensemble of Multiple Feature Selection Techniques in Credit Risk Evaluation
In credit risk evaluation the accuracy of a classifier is very significant for classifying the high-risk loan applicants correctly. Feature selection is one way of improving the accuracy of a classifier. It provide...
Improved Scatter Search Using Cuckoo Search
The Scatter Search (SS) is a deterministic strategy that has been applied successfully to some combinatorial and continuous optimization problems. Cuckoo Search (CS) is heuristic search algorithm which is inspired by the...
Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method
We propose an off-line analysis method in order to discriminate between motor imagery tasks manipulated in a brain computer interface system. A measure of large-scale synchronization based on phase locking value...