Regularization

Overview and Rationale

In order to consolidate your theoretical knowledge into technique and skills with practical

and applicational value, you will use the glmnet() package in R to implement LASSO

function to build linear and logistic models through LASSO over values of regularization

parameter lambda.

Course Outcomes

This assignment is directly linked to the following key learning outcomes from the course

syllabus:

? Conduct regularization method for models to describe relationships among

variables and make useful predictions

Assignment Summary

Use one of the real world example data sets from R (not previously used in the R practice

assignment) or a dataset you have found, to build regularization models by using Lasso

(least absolute shrinkage and selection operator) and extend Lasso model fitting to big data

that cannot be loaded into memory. You will fit solution paths for linear or logistic

regression models penalized by Lasso over a grid of values for the regularization

parameter lambda.

Use the resources in this module to guide your R code development.

Report

Your assignment/project should have a good cover/title page, introduction of what the

goals of the project and the methods you use. It also should follow APA format with at least

1000 words (excluding title page and references page) and references page. In the body of

your project you should incorporate the R codes and R outputs with interpretation of your

results. Be sure to show all the elements in the official hypothesis, including the null and

alternative hypothesis, the critical values, calculation of the test statistics and p-values.

Finally, you need to make sense of your results to make good points with proper

conclusions, to show your understanding of the course material and its application to the

dataset.

Graphs, figures, charts, tables are very useful to increase visual effects to impress your

readers. You also should do your best to give insight and understanding to the project with

a good conclusion. Please use subtitles to make your assignment more reader friendly as

well.

Assignment Rubric

Category Meets Standards Approaching Standards Below Standards

Introduction

Introduction provides a

brief and intelligible

overview of the goals and

methods of the

assignment

Introduction provides an

overview of the goals and

methods of the

assignment, but is

ambiguous or not concise

Does not introduce

project goals, project

questions or methods.

Analysis

Provides all R code and

the outputs. Includes

interpretation of the

output, graphs, figures,

charts, and tables and the

significance of the results

in the analysis.

Provides R codes and

outputs, but the R code

does not match the

outputs or is missing

some code or outputs.

Includes limited

interpretations, charts,

and tables and the

significance of the results

in the analysis.

Does not provide R code

or its outputs or minimal

R code is provided.

Includes few

interpretations, charts, or

tables. Does not identify

the significance of the

results in the analysis

Data

Visualizations

Data visualizations are

appropriate for the level

and type of analysis.

Graphs, figures and tables

communicate insights and

significance to the reader.

Data visualization are

useful for the level and

type of analysis, but

graphs, figures and tables

do not clearly

communicate significance

of the results to the

reader.

Data visualization are

used minimally or not at

all. If graphs, figures and

tables are used, it is

unclear what they are

intended to communicate

or why.

Interpretation &

Conclusions

The conclusion

summarizes and makes

sense of the results,

making good points that

reflect clear

understanding of the

assignment material.

The conclusion

summarizes and makes

sense of the results,

making good points that

reflect a basic

understanding of the

assignment material.

The conclusion does not

summarize or attempt to

make sense of the results.

Conclusions do not reflect

an understanding or

reflect a

misunderstanding of the

material

Report: Writing

Mechanics, Title

Page, & References

There are no noticeable

errors in grammar,

spelling, and punctuation;

and completely correct

usage of title page,

citations, and references.

The report contains

approximately of 1000

words

There are very few errors

in grammar, spelling, and

punctuation; and

completely correct usage

of title page, citations, and

references. The report

contains approximately

1000 words

There are more than five

errors in grammar,

spelling, and punctuation;

or the usage of title page,

citations, and references

are incomplete; or the

report contains far less

than 1000 words

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