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Predictive analytics for healthcare using machine learning is a challenged task to help doctors decide the exact treatments for saving lives. In this paper, we present machine learning techniques for predicting the chronic kidney disease using clinical data. Four machine learning methods are explored including K-nearest neighbors (KNN), support vector machine (SVM), logistic regression (LR), and decision...
Functional connectivity describes neural activity from resting-state functional magnetic resonance imaging (rs-fMRI). This noninvasive modality is a promising imaging biomark-er of neurodegenerative diseases, such as Alzheimer's disease (AD), where the connectome can be an indicator to assess and to understand the pathology. However, it only provides noisy measurements of brain activity. As a consequence,...
Machine learning is an emerging technique for building analytic models for machines to "learn" from data and be able to do predictive analysis. The ability of machines to "learn" and do predictive analysis is very important in this era of big data and it has a wide range of application areas. For instance, banks and financial institutions are sometimes faced with the challenge...
Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). An adaptive fuzzy logic system model that utilizes a prototype defuzzification scheme has been...
Machine learning is the process which converts the information into intelligent actions. This paper presents a literature review on application of different Machine Learning algorithms on huge amount of data collected by the academic institutes. Predictive analytics using the machine learning algorithms has become a new tool of this modern era, as it assists academic institutions in improving the...
On-time performance during travel is a key factor in determining passenger convenience and satisfaction. On time flight arrivals and departures are dependent on various factors including airport characteristics like the number of flights handled, ground handler's efficiency, disruptions caused by weather conditions, security alerts, queue times at immigration and air traffic congestion. There is a...
Massive Open Online Course(MOOC) is undergoing explosive growth recently, both the number of MOOC platforms and courses are increasing dramatically during these years. One of the major concerns in MOOC is high dropout rate, we study dropout prediction in MOOCs, using student's learning activities data in a period of time to measure how likely students would drop out in next couple of days. We collect...
Class imbalance is a major problem in machine learning. It occurs when the number of instances in the majority class is significantly more than the number of instances in the minority class. This is a common problem which is recurring in most datasets, including the one used in this paper (i.e. direct marketing dataset). In direct marketing, businesses are interested in identifying potential buyers,...
The achievement of good honours in Undergraduate degrees is important in the context of Higher Education (HE), both for students and for the institutions that host them. In this paper, we look at whether data mining can be used to highlight performance problems early on and propose remedial actions. Furthermore, some of the methods may also form the basis for recommender systems that may guide students...
The most widely used classification techniques for whole brain image classification rely on kernel machines such as support vector machines and Gaussian processes, due to their computational efficiency, accurate prediction and suitability to tackle the combination of small sample sizes and high dimensionality that make neuroimaging data a challenging problem. Such methods generally make use of linear...
The need for higher equipment availability and lower maintenance cost is driving the development and integration of prognostic and health management (PHM) systems. Taking advantage of advances in sensor technologies, PHM systems enable a predictive maintenance strategy through continuously monitoring the health of complex systems. The core of PHM technology is prognostic which is able to estimate...
Three scoring systems were considered and described for dermatological applications in which malignant and benign skin lesions have to be recognized: two models are derived from logistic regression and naïve Bayes rule by rounding model parameters to their nearest integer values; the third approach defines the scoring system by a direct stepwise adding of the most significant binary risk factors....
Malware is any kind of program that is designed to perform malicious activity in computers and networks. To evade traditional signature-based malware detection techniques, malware developers employ obfuscation techniques. Two main type of obfuscation techniques are polymorphism and metamorphism. New approaches for detecting obfuscated malwares are commonly based on machine learning techniques to extract...
Software Analytics is gaining momentum as aresult of involved empirical research in enhancing quality andproductivity of software engineering activities. There have beenrigorous research efforts in the areas of bug prediction and testingeffort prediction by making use of historical data. The problemof predicting bug fix times is an interesting problem with lotsof advantages to industry but there have...
Every year in certain areas of a city, the population tends to grow, causing a parallel growth in need for services. These needs can be new schools, hospitals, public facilities, road expansions, public parks, etc. These needs are handled by the municipal authorities in those cities, who are representatives of the government charged with carrying out such responsibilities. In this paper, the municipal...
Carbon plays an essential role in the environment for climate change. The presence and absence of carbon directly affects all living beings. Trees inhale carbon for giving us oxygen. The environmental study of carbon is a major concern these days. Carbon Dioxide is stored in different five carbon pools of forest. Many countries are innolved in the research of environmental factors these days. The...
While training a model with data from a dataset, we have to think of an ideal way to do so. The training should be done in such a way that while the model has enough instances to train on, they should not over-fit the model and at the same time, it must be considered that if there are not enough instances to train on, the model would not be trained properly and would give poor results when used for...
The proposed work in the term is focused on developing the prediction model on crude commodity based on its price movement due to news released by various sources. Further the model is improved by applying different computing techniques. The primary objective is to derive model for investment decision for crude commodity. The decision strategy would be driven by analysing stock price fluctuation based...
There exists a base classification system for classification of problem tickets in the Enterprise domain. Different deep learning algorithms (Gated Recursive Unit and Long Short Term Memory) were investigated for solving the classification problem. Experiments were conducted for different parameters and layers for these algorithms. Paper brings out the architectures tried, results obtained, our conclusions...
A question that is often arose on career management is how to choose potential employees to become chief and achieve performance target based on employees' historical data. This research attempts to answer the question and tries to determine what factors can affect an employee to become a chief and capable to achieve performance target. To address the question, this study adopts predictive modelling...
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