Description: Provides a R driver for Apache Drill<https://drill.apache.org>, which could connect to the Apache Drill cluster<https://drill.apache.org/docs/installing-drill-on-the-cluster> or drillbit<https://drill.apache.org/docs/embedded-mode-prerequisites> and get result(in data frame) from the SQL query and check the current configuration status. This link <https://drill.apache.org/docs> contains more information about Apache Drill.

Title: Self-Drive Machine Learning Projects
Authors@R: c(person("Dayanand Ubrangala", role = c("aut", "cre"), email = "daya6489@gmail.com"),
person("Sayan", "Putatunda", role = c("aut","ctb")),
person("Kiran", "R", role = c("aut","ctb")),
person("Ravi", "Prasad Kondapalli", role = c("aut","ctb")))
Imports: sampling(>= 2.8), rmarkdown(>= 1.9), data.table(>= 1.10.4-3),
SmartEDA(>= 0.3.1) , caTools, ParamHelpers(>= 1.12), mlr(>=
Description: Implementing some of the pillars of an automated machine learning pipeline such as (i) Automated data preparation, (ii) Feature engineering, (iii) Model building in classification context that includes techniques such as (a) Regularised regression [1], (b) Logistic regression [2], (c) Random Forest [3], (d) Decision tree [4] and (e) Extreme Gradient Boosting (xgboost) [5], and finally, (iv) Model explanation (using lift chart and partial dependency plots). Accomplishes the above tasks  by running the function instead of writing lengthy R codes. Also provides some additional features such as generating missing at random (MAR) variables and automated exploratory data analysis. Moreover, function exports the model results with the required plots in an HTML vignette report format that follows the best practices of the industry and the academia. [1] Gonzales G B and De Saeger (2018) <doi:10.1038/s41598-018-21851-7>, [2] Sperandei S (2014) <doi:10.11613/BM.2014.003>, [3] Breiman L (2001) <doi:10.1023/A:1010933404324>, [4] Kingsford C and Salzberg S (2008) <doi:10.1038/nbt0908-1011>, [5] Chen Tianqi and Guestrin Carlos (2016) <doi:10.1145/2939672.2939785>.
Suggests: testthat, knitr, ranger, glmnet, randomForest, rpart,
Packaged: 2020-05-29 15:46:10 UTC; dubrangala