adefisayoa / dmproject2017

DMProject2017

NOTE: Create your own copy of R file and work on it. This will help avoid the conflicts. At the end, we'll merge them up i na master file.

Tasks:

• Data cleaning. (Done, see if there's any more need for it). filtered_data.csv is the filtered data, original.csv is the original data file.
• Data visualization. (Come up with some interesting visualizations of data that help understands the data in a better way).
• Apply all the classification algorithms that we have learnt and try to compare it's performance. (visualisations here can help too).
• Figure out if we can do classification on multiple features in one go. If yes, do it. Otherwise, we'll run the algorithms separately for 3 features (applied, disliked, liked)
• PCA and clustering maybe? (good if we can do these).