Peer Review by Junqing Zou (jz862)

[zoujunqing]

The project aims to create a model to predict whether a pending merger is successful or not. The group used data set from SDC Platinum with years between 1990 and 2016 and only included public entity targets.

Things I like about the report:

1. The group described clearly how they cleaned the data (Simplifying multiple statuses into only two status, delete samples without or with extremely low share prices, and etc.).
2. The group used appropriate models to tackle the binary classification problem like logistic regression, simple classification tree, and random forest.
3. The group set a reasonable benchmark to evaluate the model (comparing with blindly guessing "Completed").

Areas for improvement:

1. Maybe try interpolation to fill the NaNs rather than filling with zeros.
2. It would be better if there are more illustrations on the graphs. For example, what are the features in the feature importance plot?