Machine Learning Projects using Python #2.! Programming World

Section 2: Forecast the IPO Market Using Logistic Regression

2.1 The IPO Market

Before deciding strategies for the IPO market, we need to study the IPO market and derive inferences from it.

·         Read about the IPO market

·         Look at the performance of the IPO market

·         Study strategies

Click Here to Download

2.2 Feature Engineering

The consideration and inclusion of all factors affecting the market is called feature engineering. Modeling this is as important as the data used in building the model.

·         Add features. Retrieve data.

·         Tidy up the underwriter data. Add final features.

·         Transform data into matrix form

Click Here to Download

2.3 Binary Classification

Instead of giving the value of the return, you can predict the IPO for a trade you will buy or not buy. The model used is logistic regression.

·         Apply logic regression to the data

·         Split data into training and testing datasets. Fit the model.

·         Evaluate the model

Click Here to Download

2.4 Feature Importance

It is important to know which features will make the offering successful. You can find that out in this section.

·         Examine coefficients for logistic regression.

·         Fit random forest classifier.

·         Evaluate summary

Click Here to Download


Section 3