data science with R
Question Description
project 1
Problem Statement:
An education department in the US needs to analyze the factors that influence the admission of a student into a college.
Analyze the historical data and determine the key drivers. Analysis information:
Predictive • Run logistic model to determine the factors that influence the admission process of a student (Drop insignificant variables) • Transform variables to factors wherever required • Calculate accuracy of the model • Try other modeling techniques like decision tree and SVM and select a champion model • Determine the accuracy rates for each model • Select the most accurate model • Identify other Machine learning or statistical techniques that can be used
Descriptive • Categorize the grade point average into High, Medium, and Low (with admission probability percentages) and plot it on a point chart. • Cross grid for admission variables with GRE Categorization is shown below:
GRE Categorized 0-440 Low 440-580 Medium 580 + High
Variables in the Dataset:
project 2
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