peer reveiw from Mental_Health team #56
Description
This is a data analysis project financial project about IPO. This project is trying to find out the factor which can help them predict the correct IPO. In my understanding, they are trying to build a model that can help them find an optimal parameter set. The data they are using is from Kaggle called Stocks IPO information.
I really like this project! This project is focusing on the big profitable but also unstable, and seems unpredictable project. Therefore, the problem of IPO is very suitable for a big messy data analysis project. The data set they choose is also very good. The data set is very informative. It covers almost all the factor which will affect the IPO. I also like the criteria of a successful IPO they set up in the problem statement, which helps them clearly explain their project result.
There are three parts I am a little bit concerned about:
- The size of the data is not very big(only about 3000). This means the training set of the model may not be very big. As a result, the result of the model may not be very good.
- The informative data set have many features. They may need to spend plenty of time on feature engineering to help them save the computation source and get a good model.
- Need more clarification about the meaning of the "reliable". (for example: is the reliable means stable? accurate? most related?)