Python Decision Tree Project

This project has two parts:

Given a .cvs file (see uploaded filed [login to view URL]) for each unique VideoFileID the data would be vectored. Here is a psudeo code sample in R.

ld <- lapply(split(d[-1], d[["VideoFileId"]]), unlist)

ldNames <- Reduce(unique, lapply(ld, names))

[login to view URL](rbind, lapply(ld, function(x) x[ldNames]))

d2 <- [login to view URL](rbind, lapply(ld, function(x) x[ldNames]))

ldNames_sorted <- c(matrix(ldNames, ncol = (ncol(d) - 1), byrow = TRUE))

d2[, ldNames_sorted]

[login to view URL] = [login to view URL](VideoFileId = [login to view URL](d2), d2)

The second part of the project is to take this output file and write a python based supervised learning model. The model would allow for 80% of the data to be used for training and 20% for testing. The Model will be considered "complete" when the results return an Area under the ROC ( Receiver Operating Characteristic) Curve greater than 0.9.

Beceriler: C Programlama, C++ Programlama, Makine Öğrenimi, Python, Yazılım Mimarisi

Daha fazlasını gör: sklearn decision tree visualization, decision tree python library, decision tree classifier example, decision tree python code example, decision tree entropy python, python id3 decision tree implementation, decision tree python code from scratch, decision tree algorithm, project decision tree, python predict outcome event decision tree, decision tree test data set, python decision tree learning, decision tree python github, decision tree python from scratch, decision tree python, decision tree python code, decision tree algorithm python, decision tree sample data set, decision tree implementation in python, decision tree implementation in python from scratch

İşveren Hakkında:
( 0 değerlendirme ) Williamsburg, United States

Proje NO: #18901709



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