DanielT_LIS4370.Rprog

Daniel Tafmizi Dr. Friedman Lis 4370 Module 12 Github:  daniel.R/Work.R/LIS4370Rprog/mod12.Rmd at main · DanielDataGit/daniel.R I have been using the R-markdown structure in my Data and Text Mining course. Having this practice, I have become familiar with the structure and html output. One new thing I learned was the kable function. This offers a visually appealing way to structure an R table output. I am excited to test more knitr functions while creating vignettes for my final project. I think RMD's are a great way to teach users how a package works.

Daniel Tafmizi Dr. Friedman Lis 4370 Module 11  Github:  daniel.R/Work.R/LIS4370Rprog/debugR.R at main · DanielDataGit/daniel.R When debugging I came across two error statements. The line " outliers [,j ] <- outliers [,j ] && tukey.outlier (x [,j ])  " resulted in error messages. To resolve this problem, I wrote "outliers[j] <- all(outliers [,j ])". This fixed the logical coercion and the lack of a tukey.outlier function . Since we have no method for detecting outliers, this just makes it so that the answer is TRUE for all.  

Daniel Tafmizi Dr. Friedman Lis 4370 Module 10 Github:  daniel.R/Work.R/LIS4370Rprog/finalproject/DESCRIPTION at main · DanielDataGit/daniel.R     For my final project, I would like to incorporate the fellowship project. In it, I will determine the architecture of my fellowship project, as well as start to compile techniques for ML modelling and its respective visualizations. I plan to define techniques for supervised ML, broken down into classification and regression. I hope to make this as beginner friendly as possible, as I have had and continue to have my fair share of troubles dealing with the ML jargon found in professional sources. Overall, I hope to mimic the scikit-learn python library in a more R/beginner friendly way. If the fellowship project heads in a different direction, this project will still act as a great step in understanding how I can frame different elements for ML visualization.