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This article proposed ‘TLiSVM’ or ‘3LiSVM’ (Triple Linear SVM Weight) as an alternative technique for dimensionality reduction with a Support Vector Machine (SVM) classifier on a two-class dataset. The efficiency of TLiSVM was compared with two chosen techniques, including Linear SVM Weight (LiSVM) and Double Linear SVM Weight (DLiSVM). Three datasets, including DLBCL, Duke Breast-Cancer and Leukemia,...
The watershed rehabilitation success rate have not been up, is the result of policies in watershed rehabilitation strategies that are less precise. From the above problems, we need a study that can provide a reference or any other alternative in determining priority watersheds to be rehabilitated, one through data mining. This paper uses a case study of Watershed data which are grouped using K-modes...
Poverty was a problem that faced by many developing countries, especially Indonesia. One way to resolve the issue of poverty through social assistance provided by the government. Besides that, knowing the factors affecting poverty in the region was also important to determine the strategic plan to reduce poverty in Indonesia. Data mining approach was used to determine the classification model. The...
Research papers are often referred by researchers. But finding the desired or relevant research paper quickly and accurately is very difficult. As there are lot of research papers in given dataset and keeps enormously increasing. There is a need to avail automated processing approach for tackling such a huge volume of dataset to retrieve relevant papers accurately. This paper proposes a framework...
With the rapid growth of Internet consumption, the various product comments' form and redundant information are not convenient for the customers to grasp the hot opinions of the historical comments. In view of this, this paper studies the hot opinions of the products' comments and takes the hotel comments data as the main research objects. We filter the comment data from the length of the comments...
The rapid growth of information technology along with variety of digital data generation provides an opportunity to better understand human dynamics. However, knowing and obtaining complete information about events and activities that happen, becomes a complicated task in Natural Language Processing (NLP) and location based social networks. In this research, we introduce a new approach to recognize...
When a data holder wants to share databases that contain personal attributes, individual privacy needs to be considered. Existing anonymization techniques, such as l-diversity, remove identifiers and generalize quasi-identifiers (QIDs) from the database to ensure that adversaries cannot specify each individual's sensitive attributes. Usually, the database is anonymized based on one-size-fits-all measures...
Glacier thickness change is a sensitive factor in response to global climate change, its quantitative assessment is critical to evaluate the variation of glacier mass balance. This paper analyzed and improved the method of planes fitted to repeat-tracks which uses Geoscience Laser Altimeter System (GLAS) data to extract glacier thickness change and applied it in the Tibetan Plateau area. The original...
Machine learning has become a powerful tool in real applications such as decision making, sentiment prediction and ontology engineering. In the form of learning strategies, machine learning can be specialized into two types: supervised learning and unsupervised learning. Classification is a special type of supervised learning task, which can also be referred to as categorical prediction. In other...
For many years, the relevant analyses have indicated problems in the functioning of the Croatian small-sized enterprises sector. It has been marked by recession, changes in legislation, financing problems, poor cash flow, dependence on large and state-owned companies and the low rate of survival. At the same time, the small-sized enterprises sector has been referred to as a generator of economic development,...
Mining Ancient Chinese corpus is not as convenient as mining modern Chinese, because tokenizers perform poorly on them for lack of a complete dictionary of ancient Chinese words. So finding an effective way to find all words of these texts is significant. In this paper, we treat unknown word detection as a binary classification task, and propose new effective features for classification, including...
Process Mining aims to extract information from event logs to highlight the underlying business processes. It is useful in situations where there is no detailed and complete knowledge of how an overall system works, such as in a hospital where most processes are complex and ad-hoc. Many Process Mining discovery techniques have been proposed so far, but many challenges are still to be faced. Implicit...
In protein structure, knot is a vital part. Structures that contain a knot formed by the path of the polypeptide backbone represent some of the most complex topologies observed in proteins. Detecting these knots, we hope to find out some information or chances to cope with protein malfunction or abnormalities. There are some state of the art algorithms to find knot in a protein structure e.g. KNOT...
Students academic performance is the reflection of both academic background and family support. This performance record is critical for the educational institution because they can learn from this to improve their quality. Educational data mining helps to analyze these data and extract information from it. We can determine the status of learners academic performance. For achieving this we can use...
This paper illustrated the use of the Cubic spline Technique (CST) to analyze the EEG signals. It is provides full description of the extraction of the knots of EEG signals and then a discussion of how to select the optimum location of the knot and reducing the knots. Also the paper discussed that the feature extracted dependent on the optimal position of the knots. The initial results show the highest...
Laboratory blood test is the term of abnormalities examination in human blood. DHF (Dengue Hemorrhagic Fever) disease and TF (Typhoid Fever) are both will cause a fever, to be sure the patient should perform blood tests. Data source used in this research came from the hospital medical record which recorded patient's laboratory blood test results. Recapitulation of the laboratory blood test results...
This paper introduces the multiple linear regression, stepwise linear regression, neural network method, and improves the neural network. Comprehensive analysis of the current prediction methods, the application principle of a detailed analysis and comparison of the various prediction methods advantages and disadvantages. Put forward to improve short-term load forecasting accuracy is not only attach...
The discrete topology optimization method is widely used because of its high degree of freedom and high problem-solving efficiency. However, one of its main drawbacks is that the output graphic is constituted of a 0–1 matrix leading to rough boundaries and implicit structures, which are difficult to be manufactured. Aiming to transform the implicit rough boundary into the explicit smooth boundary...
Vocational is one of education types in Indonesia. Graduates from vocational school need to have enough motivation to get into working environment either as employees or as entrepreneurs. In vocational education, it is important to monitor students' motivation and achievement. It will help to understand students' condition and give an overview in setting the appropriate program for the students. This...
The Direct Selling Industry in the Philippines is continuously growing as more people become direct sellers. With this, the ability of direct selling companies to manage its sellers will be a challenge. Customer Lifetime Value (CLV), or the monetary value a customer is expected to contribute to the company before churning, is one measure that can be used as a basis for managing customers and for this...
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