In a standard text classification (TC) study, preprocessing is one of the key components to improve performance. This study aims look at how effects TC according news text, language, and feature selection. All potential combinations commonly used techniques are compared on domain, namely data, in two different datasets for this aim. Preprocessing technique contributions performance multiple siz...

Abstract In literature, the machine learning-based studies of sentiment analysis are usually supervised learning which must have pre-labeled datasets to be large enough in certain domains. Obviously, this task is tedious, expensive and time-consuming build, hard handle unseen data. This paper has approached semi-supervised for Vietnamese limited datasets. We summarized many preprocessing techni...

In this paper we summarize various possible techniques such as Crossover Prediction Model or the classical Principal Component Analysis (PCA) tool to include exogenous data. Furthermore we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in ...