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SMOTE (Synthetic minority over-sampling technique) is a commonly used over-sampling technique to subside the imbalanced dataset problem. Traditionally SMOTE has two key important parameters, one is to control the amount of over-sampling, and the other specifies the area of the nearest neighbors. These two parameters are arbitrarily chosen by user. So there are no universally best default values. In...
Sentiment analysis emerged as an important computational domain to gain insights from snippets of texts, as social media recently gained popularity. Text mining has long been a fundamental data analytic for sentiment analysis. One of the popular preprocessing approaches in text mining is transforming text strings to word vectors which form a high-dimensional sparse matrix. This sparse matrix poses...
Endurance sport events have increasingly been gaining the popularity. Every year, more and more amateur athletes decide to participate in such events. During the race, proper eating is one of the most important components for achieving the good finish time and in this respect also the good place. In this paper, we examine possibility to predict what to eat at the moment. In line with this, machine...
Sentiment analysis in text mining is known to be a challenging task. Sentiment is subtly reflected by the tone, affective state or emotion of a writer's expression in words. Conventional text mining techniques which are based on keyword frequency counting usually run short of accurately detecting such subjective information implied in the text. In this paper we evaluated several popular classification...
The prediction of rare events is a pressing scientific problem. Events such as extreme meteorological conditions, may aggravate human morbidity and mortality. Yet, their prediction is inherently difficult as, by definition, these events are characterised by low occurrence, high sampling variation, and uncertainty. For example, earthquakes have a high magnitude variation and are irregular. In the past,...
Trend following plays an important role in technical analysis for trading financial instruments. In this paper, we propose a model based on Float-encoding Genetic Algorithm (FGA) to determine the best thresholds for trend following in financial time series. Trend following is based on the thresholds called P&Q which is calculated from the amount of an uptrend and downtrend to determine when to...
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