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BIF524/CSC463 Data Mining Project – Phase 2 Solved

Original price was: $40.00.Current price is: $35.00.

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Description

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Description

The project is split into three phases that match the learning outcomes throughout the
course. Each phase accounts for 10% of your total grade.

Guidelines:

The aim of this project is to demonstrate your ability to apply and discuss the outcomes
of various data mining techniques on a problem and a dataset of your interest.
 The dataset must include quantitative and qualitative attributes.
 Your work should not be limited to what you learn in the practical sessions of the course.
 You must submit an R markdown, knitted as a pdf file, for every phase.
 You can work in a group of two – same group in all phases.
 Your grade will be subject to a 5% penalty for every day of submission delay.
– Phase II: (10%) due Wednesday, Nov. 15, 11:59pm.
 Choose a dataset with a quantitative response, and discuss your choice with me. (1%)

 N.B. Your dataset should not be associated with any existing work related to the
required tasks – e.g., on kaggle, Github, …
 Apply logistic regression, linear, and quadratic discriminant analysis techniques. (4%)
 Include resampling techniques in your work, and compare the performance of the generated
classifiers accordingly. Use appropriate comparison measures, tables, and graphs. (3%)
 Use subset selection approaches with different measures. (3%)

For each phase, make sure to highlight the following in your R markdown pdf file:
 Dataset description including context and features
 Data mining tasks
 Model performance
 Results
 Comparison of results
 Comments and interpretation
Name of your R markdown pdf file following this template: NameOfTeamMember1-
NameOfTeamMember2_Phase PhaseNumber.