Data Mining Lab

In a team of three:

• During the course, we went through the whole path of data mining from dataset preparation up to meaningful predictions.
• It included the following steps: dataset search and description, understanding the data and naive introspection, feature construction and selection and prediction and evaluation.
• We worked on the Mashable dataset from UCI repository. After finding inconsistencies in the dataset we rebuild the dataset ourselves. We did descriptive analysis and text mining on the data and prepared our final features. Our final goal was to predict the number of shares on social media that reflects an articles’s popularity and give recommendations to the author in case the prediction is unpopular.
• Tools: Python, R