I need help with ideas for a proposal for a data mining project using R. I am really just looking for some examples and an explanation on how different algorithms or techniques can be used to analyze the data. These are the instructions:

For your project, you carry out data mining on a large dataset and analyse the results. Your final report will be in the form of a presentation on the project.

Implementation of the projects should be done using R programming language. No other programming languages for the project implementation will be accepted. It is strongly recommended that you continue to use the RStudio tool that you have been using throughout this module.

The dataset used in the project should be reasonably big (1k+ rows/instances). You can either find and propose a dataset to use or choose a dataset from data set repository.

You should identify one or more data mining algorithm/technique to use and apply in your project. The following are proposals of algorithms/techniques students can choose from (but you can also use something else):

o KNN (K Nearest Neighbourhood)

o Bayesian methods

o Neural networks

o Linear regression

o Sentiment analysis