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This data set was used in my master thesis "Reproducibility of Machine Learning results". On one hand, this dataset was used as an input in creating Support Vector Machine , Naive Bayes and Random Forest models in R, Python, RapidMiner and Weka in order to experiment the influence that different development environments have on reproducibility of machine learning results. Furthermore all the models implemented in all of previously mentioned environments were tested in different operating systems such as Windows, Linux and Mac OS.
machine learning results, Reproducibility
machine learning results, Reproducibility
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 7 | |
| downloads | 1 |

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