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This paper proposes a novel ensemble method to improve the performance of binary classification. The proposed method is a non-linear combination of base models and an application of adaptive selection of the most suitable model for each data instance. Ensemble methods, an important type of machine learning technique, have drawn a lot of attention in both academic research and practical applications,...
Titanic disaster occurred 100 years ago on April 15, 1912, killing about 1500 passengers and crew members. The fateful incident still compel the researchers and analysts to understand what can have led to the survival of some passengers and demise of the others. With the use of machine learning methods and a dataset consisting of 891 rows in the train set and 418 rows in the test set, the research...
In order to survive the fierce competition in today's telecommunication industry, it is mandatory to understand the need of customers who might think to move toward another competitor. Thus, assessing the churn prediction, which becomes a real concern in the telecom industry, is critical in predicting future trends of the industry. In this work, we wanted to determine the best and reliable prediction...
In Machine Learning, we often encounter instances of imbalanced data which occur whenever there is an unequal representation in the classification categories. New found interest in Machine Learning has made its usage ubiquitous. Its applications encompass a wide plethora of scenarios ranging from Business and Banking to Bioinformatics and Psychology. These problems are often characterized by imbalanced...
Intensive Care Unit (ICU) admission is a major factor that affects the healthcare budget. ICU cost is extremely high because its resources are consumed through highly advanced equipment providing quality healthcare service for patients. Thus, the need for a predictive model for the decision to transfer stroke in-patients to the ICU is very important. Also, this predictive model will help to lower...
There have been a lot of researches that demonstrate the phenomenon of life or the origin of the disease and classify or diagnose the state of the cell. These are usually achieved by the strength of the gene expression under certain circumstances by the microarray which can observe tens and thousands of gene expression profile. It is not feasible to use all the attributes because a lots of gene expression...
Methods of artificial intelligence have been widely used in the study of investment related topics, and the methods adopted include genetic algorithm and neural network, etc. However, as different to the methods taken in the past, support vector machine is adopted in this article to perform investment strategy study for domestic stock market; investment strategy can be divided into three strategies...
In this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. We choose one set of product related and one set of process related software metrics and use them for classifying Java files of the Eclipse project as defective respective defect-free. Classification models are built using three common machine learners: logistic regression,...
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