Performance Analysis of Classification Learning Methods on Large Dataset using two Data Mining Tools

Data is increasing day to day thus, processing this data and selection of right method and tool is really a big problem. Computer scientists are processing and analysing data on different machine learning methods using various Data Mining tools to get the high accuracy of results and minimum time for building of Model. There are several data analysis and processing tools like WEKA, RapidMiner, Keel, and etc. available for the purpose of processing, analysis, modelling and etc. Still no single tool is perfect or nominated for data processing and analysis. In this concern, the authors present here a comparative and analytical research study on the performance of different classification machine learning algorithms like Naïve Bayes, KNN, IBK, Random Forest, C4.5, J48 and Data Mining tools which are WEKA and RapidMiner on a large datasets to evaluate their performance and analytical results with low cost of error. The data set Adult Income is taken from UCI Data repository for this research study. The significance and aim of this study is to evaluate and assess the range of performance of different machine learning methods and two diverse data mining tools on dissimilar datasets. The result of each classification method and Data mining tool is analysed and presented in the end

Performance Analysis of Classification Learning Methods on Large Dataset using two Data Mining Tools

Data is increasing day to day thus, processing this data and selection of right method and tool is really a big problem. Computer scientists are processing and analysing data on different machine learning methods using various Data Mining tools to get the high accuracy of results and minimum time for building of Model. There are several data analysis and processing tools like WEKA, RapidMiner, Keel, and etc. available for the purpose of processing, analysis, modelling and etc. Still no single tool is perfect or nominated for data processing and analysis. In this concern, the authors present here a comparative and analytical research study on the performance of different classification machine learning algorithms like Naïve Bayes, KNN, IBK, Random Forest, C4.5, J48 and Data Mining tools which are WEKA and RapidMiner on a large datasets to evaluate their performance and analytical results with low cost of error. The data set Adult Income is taken from UCI Data repository for this research study. The significance and aim of this study is to evaluate and assess the range of performance of different machine learning methods and two diverse data mining tools on dissimilar datasets. The result of each classification method and Data mining tool is analysed and presented in the end

Constructing Ghost Free High Dynamic Range Images Using Convolutional Neural Network and Structural Similarity Index

A foreign object, commonly called as a ghost artifact, is integrated in the HDR output image when there is a moving object in the photography scene. The problem is persisting even after numerous models proposed by researchers. The most advanced techniques for capturing HDR photographs are still struggling with the produced output till date. The majority of the existing techniques are unable to tackle the situation where luminance varies in the input images. This ultimately causes the algorithms to compromise on quality by reducing the input images. In this research, two techniques are presented that help in getting rid of ghost artifacts from HDR output. The first method that is used in this research is a vintage method that uses structural similarity index measurement. The second method is using Convolutional Neural Network which is proved to be the best configuration of neural network for image recognition purposes. The first method using structural similarity is based on the vintage method of matching two images. This method works by comparing the objective image with the reference image and the algorithm estimates the degree of similarity in the context of luminance, contrast, and structural information. The second method is the use of a convolutional neural network. Since a convolutional neural network is a specialized tool for image processing, a convolutional neural network is designed and trained to estimate the index of similarity of two or more images

Comparative analysis of payment system and suggesting solutions for data security issues in Pakistan

The payment system has been the back bone of financial systems of a country. The stability and growth of an economy is directly related to the strength, reliability, scalability and efficiency of payment system. There are various kinds of instruments and channels in payment system; some are slow like paper cheques and some electronic transfers. And after the introduction of Electronic payment methods and their wide spread acceptance in many developed countries has played an important roles in stabilizing and growing their economies. But the use of electronic payment methods is still in infancy in Pakistan due to various incidents of frauds and identity thefts. In Pakistan only 12% of population has access to Bank branches but internet is available in almost every small town and mobile penetration is almost 80-90% of population. Currently there are two major systems payment systems i.e. one is using clearance of amount based on settlement of Physical cheques drawn between difference banks and second is using online interbank fund transfer . The second one is also divided into two segments. i.e. large and small amounts of transaction. Larger transactions having no limit of amount are conducted between Banks using Real Time Gross settlement Systems (RTGS ) managed by Stat bank of Pakistan and the other is using Online Interbank fund transfer for small payments having limitation of 250,000 (Two lacs fifty thousand rupees) categorized as retail payment systems. The cost of transfer for large amount is only 50 Rupees per transaction regardless of amount, but an ordinary customer has to be a good business client of bank to carry out transfer of amount online. The cost of low amount using interbank online transfer is at least 50 Rupees and goes up with amount of transfer. The service fee or cost is also different among various payment methods. The major cost on cheque clearing is TIME which is from 24 hours to 36 Hours and this is the costlier methods. Further the movement of cheques between banks and central clearing house is a great threat in current situation of law and order. The amount written on cheques and the name of beneficiary and issuer could be the possible data security issue. So this is major issue in terms of cost , efficiency and data security. In this study the emphasize would be to evaluate the problems in this section and to suggest more secure and efficient system. So this study is aimed at to suggest secure, efficient and reliable method of payment system

Performance Analysis of Table Driven and Event Driven Protocols for Voice and Video Services in MANET

This research paper encompasses the performance analysis of table driven and event driven routing protocols by using voice and video traffic in mobile Adhoc network (MANET). Particularly, OLSR (table driven) and DSR (Event driven) protocol are considered. The nodes of MANET establish the connections with each other energetically and can move freely in any direction. In mobile Adhoc network, environment event driven and table driven protocols have significant subject matter of study. There is a mobility issue which matters the service performance due to breakage and renewal of links of mobile nodes. Protocols performance has significance on overall performance of MANET. The aim of this study is to present the performance analysis of selected routing protocols by varying the node densities and WLAN physical characteristics. The voice and video traffic applications are configured discretely by using OLSR and DSR in scenarios. Moreover, for the performance observation the parameters are jitter, traffic received, traffic sent, end-to-end delay, traffic load, and throughput. The simulations have been carried out through OPNET 14.5 modeller tool and results has been analysed

Performance Analysis of Table Driven and Event Driven Protocols for Voice and Video Services in MANET

This research paper encompasses the performance analysis of table driven and event driven routing protocols by using voice and video traffic in mobile Adhoc network (MANET). Particularly, OLSR (table driven) and DSR (Event driven) protocol are considered. The nodes of MANET establish the connections with each other energetically and can move freely in any direction. In mobile Adhoc network, environment event driven and table driven protocols have significant subject matter of study. There is a mobility issue which matters the service performance due to breakage and renewal of links of mobile nodes. Protocols performance has significance on overall performance of MANET. The aim of this study is to present the performance analysis of selected routing protocols by varying the node densities and WLAN physical characteristics. The voice and video traffic applications are configured discretely by using OLSR and DSR in scenarios. Moreover, for the performance observation the parameters are jitter, traffic received, traffic sent, end-to-end delay, traffic load, and throughput. The simulations have been carried out through OPNET 14.5 modeller tool and results has been analysed

Analysis Of Routing Protocol Metrics In MANET

This research paper work is about the analysis of routing protocol metrics in MANET. The routing protocols metrics are important subject matter in the mobile Adhoc network environment. The MANET environment connecting devices or nodes with each other energetically and develop mobile Adhoc wireless network . It offers the mobility to network devices to freely move in any direction and develop connection to any device. The aim of this research paper is to analyze the routing protocol metrics as, radio range, delay, load, media access delay and throughput by evaluating the simulation of AODV, DSR and TORA routing protocols using video conferencing application. The simulation results have been carried out through OPNET 14.5 modeler tool, however scenarios created, having different node densities and different WLAN physical characteristics and routing protocol metrics and analyzed results

Classification and Comparison of Hepatitis-C using Data Mining Technique

The major focus in this paper is to get the factors that shows the significance in predicting the risks of virus of hepatitis-C. 2 datasets were used for this purpose the first one is gathered from UCI Repository and the second one is taken from Zahid Medical Centre with the help of Dr. Abdul Fateh. There are nineteen features and a class feature with classification in binary. The first data set that is gathered from UCI repository contains 155 records with missing values in most of them in order to reduce this technique of normalization is applied. Now for qualitative approaches for data reduction as well as quantitative the binary logistic regression is used. The first result gathered from the Zahid Medical Centre gave us 58% accuracy result using these techniques. And second result using these procedures produced about 90% accurate classification. Our approach gives good classification rate only by using total 37% fields

Channel Assignment Algorithms and Strategies for Wireless Mesh Networks

This research report is about providing a solution to the problem of channel assignment in the multi radio wireless mesh networks that have an ad hoc based infrastructure. The aim was to minimize the fractional interference so that throughput can be maximized. The algorithms to solve this problem were classified and explained how they work. A description of channel assignment techniques is given along with a brief comparison in the literature. Main focus was towards the use on genetic algorithm. It also gives a detailed explanation of how genetic algorithm could be implemented in order to solve this problem along with conflict graphs being made by running functions in MATLAB