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Lee, Sangkeun (Matt) committed Dec 4, 2019
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Expand Up @@ -39,7 +39,7 @@ ASCENDS is a toolkit that is developed to assist scientists (or any persons) who

![Using Ascends via its command-line interface](./logo/command-line-ui.png)

Users can perform three major tasks using ASCENDS as follows. First of all, users can easily perform correlation analysis [@ezekiel1930methods] using ASCENDS. ASCENDS can quantify the correlation between input variables ($X$) and an output variable ($y$) using various correlation coefficients including Pearson's correlation coefficient [@sedgwick2012pearson] and maximal information coefficient [@kinney2014equitability]. Second, users can train, test, save and utilize classification models [@ren2003learning] without any programming efforts. For instance, with ASCENDS, by executing a single command in a terminal, user can train a model for predicting whether an email is a spam or not-spam. Last, similarly, users can train, test, save and use regression models [@darlington1990regression]. For instance, ASCENDS can be used to train a model for predicting the value of a house based on square footage, number t bedrooms, number of cars that can be parked in its garages, number of storages.
Users can perform three major tasks using ASCENDS as follows. First of all, users can easily perform correlation analysis [@ezekiel1930methods] using ASCENDS. ASCENDS can quantify the correlation between input variables ($X$) and an output variable ($y$) using various correlation coefficients including Pearson's correlation coefficient [@sedgwick2012pearson] and maximal information coefficient [@kinney2014equitability]. Second, users can train, test, save and utilize classification models [@ren2003learning] without any programming efforts. For instance, with ASCENDS, by executing a single command in a terminal, a user can train a model for predicting whether an email is a spam or not-spam. Last, similarly, users can train, test, save and use regression models [@darlington1990regression]. For instance, ASCENDS can be used to train a model for predicting the value of a house based on square footage, number t bedrooms, number of cars that can be parked in its garages, number of storages using the provided graphic user interface in a web browser.

Earlier versions of Ascends have been used for scientific research such as [@shin2019modern] [@shin2017petascale] [@wang2019machine].

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