Programming Homework Help

So just using the KNN model to predict the question which is “predict the gold spent for the players in a match of DOTA 2?”

Here is the requirement and what need to be completed:

Choose and apply one method/technique (either classification or regression) to your dataset to develop a
predictive model that will answer your question. The choice of method/technique could be Generalized Linear
Model framework based regressions or classification, kNN algorithm based classification or regression, or a tree-
based classification or regression method. Complete a report by incorporating the following elements:
A. Cover Page: Provide Title and name of group participants.
B. Project Task Status: List the tasks completed, and planned tasks for next week.
C. Executive Summary: This will introduce the objective(s) of the project and the main result from the
implementation of first predictive model. Refine the previously written summary as needed.
D. Introduction: Describe in detail the problem, the dataset(s) and the technique. At this stage this section needs
to be elaborate with as much details as possible. This section can have subsections to address each of the
component (i.e., overview of the problem, dataset(s), and the technique).
E. First Prediction Model
a. Implementation Approach: Describe what you did, how you did it, and why you did it. Code snippets
could be used to support your description, however, do not copy/paste your entire code chunk. Describe
the data pre-processing steps conducted to prepare clean dataset for analysis (model prediction and
evaluation). The data pre-processing also includes splitting of original data to separate subsets specific to
each project member. This would allow estimation of different versions of same analytical model.
Describe the logic behind your analysis; the tools you used (e.g., R packages and functions) and the
reasoning for using the chosen tool.
b. Data Analysis and Results: Each project member should explain their own analysis results (the most
important part of your report). Make appropriate use of graphs and tables to support your conclusions.
Ensure that graphs and tables are properly formatted and have professional look & feel (revise your R
code where necessary to produce clean results tables and graphs). Do not simply copy and paste the
output of the commands and functions you used.
c. Discussion: First, provide a comparative discussion of all model versions and choose the best one for
recommendation. Next, identify literature that has examined prediction models in similar context and
discuss the group’s recommended model vis-à-vis prior literature based models.
F. References: Use APA style for in-text citations and listing these cited all articles (books, journal articles,
trade publications, and applicable web sites). Avoid citation of programmer or user written webpages or
websites for technical content, instead refer to original source such as books or journal/ trade articles.