… in machine learning. … their software tools. These ensembles are described in detail within
their variants and improvements available in the literature. Their online-available software tools …

… learning problems and approached in terms of learning algorithms. This paper deals with the
subject of applying machine learning in software … utilized machine learning algorithms. We …

… open source sharing of machine learning software can play a … machine learning methods
in other disciplines and in industry. However, incentives for polishing and publishing software …

… machine learning components than for software engineering modules. Machine learning …
during training and tuning, even if the software teams building them intended for them to remain …

… Machine learning techniques are evolving rapidly, but face … clarify the software engineering
challenges for machine learning … by the Software Engineering Body of Knowledge (Swebok). …

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… To minimize the impact of the computational demands of statistical machine learning tools
and our capture software, participants worked alone on a computer with two quad-core Xeon …

… software: Alteryx, TIBCO Data Science, RapidMiner and WEKA, their capacities for data
mining processes and a description of the algorithms and techniques of machine learning that …

… In this paper, we present techniques using machine learning for automated detection of
vulnerabilities in C and C++ software1. We focus on vulnerability detection at the individual …

… tools available for Data Mining and Machine Learning, followed by the description, pros and
cons of these tools… DM tool is presented as open source software with three features [2]. The …