Prediction of Mental Health Problems Among Children Using Machine Learning Techniques
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 1
Abstract
Early diagnosis of mental health problems helps the professionals to treat it at an earlier stage and improves the patients’ quality of life. So, there is an urgent need to treat basic mental health problems that prevail among children which may lead to complicated problems, if not treated at an early stage. Machine learning Techniques are currently well suited for analyzing medical data and diagnosing the problem. This research has identified eight machine learning techniques and has compared their performances on different measures of accuracy in diagnosing five basic mental health problems. A data set consisting of sixty cases is collected for training and testing the performance of the techniques. Twenty-five attributes have been identified as important for diagnosing the problem from the documents. The attributes have been reduced by applying Feature Selection algorithms over the full attribute data set. The accuracy over the full attribute set and selected attribute set on various machine learning techniques have been compared. It is evident from the results that the three classifiers viz., Multilayer Perceptron, Multiclass Classifier and LAD Tree produced more accurate results and there is only a slight difference between their performances over full attribute set and selected attribute set.
Authors and Affiliations
Ms. Sumathi M. R. , Dr. B. Poorna
Keywords
Related Articles
- EP ID EP112174
- DOI 10.14569/IJACSA.2016.070176
- Views 141
- Downloads 0
OPTIMIZING THE USE OF AN SPI FLASH PROM IN MICROBLAZE-BASED EMBEDDED SYSTEMS
This paper aims to simplify FPGA designs that incorporate Embedded Software Systems using a soft core Processor. It describes a simple solution to reduce the need of multiple non-volatile memory devices by using one SPI...
An Approach for Energy Efficient Dynamic Virtual Machine Consolidation in Cloud Environment
Nowadays, as the use of cloud computing service becomes more extensive and the customers welcome this service, an increasing trend in energy consumption and operational costs of these centers may be seen. To reduce opera...
Implementation of ISS - IHAS (Information Security System-Information Hiding in Audio Signal) model with reference to proposed e-cipher Method
This paper shows the possibility of exploiting the features of E- cipher method by using both cryptography and Information hiding in Audio signal methods used to send and receive the message in more secured way. Proposed...
Competitive Sparse Representation Classification for Face Recognition
A method, named competitive sparse representation classification (CSRC), is proposed for face recognition in this paper. CSRC introduces a lowest competitive deletion mechanism which removes the lowest competitive sample...
The Implementation of Software Anti-Ageing Model towards Green and Sustainable Products
Software ageing is a phenomenon that normally occurs in a long running software. Progressive degradation of software performance is a symptom that shows software is getting aged and old. Researchers believe that the agei...