Chapter 4, Data Cleansing and Preliminary Data Analysis

1. Instead of building the decision tree manually, it would be interesting to study in-depth the example built-in Azure Machine Learning Studio, which was shown in Chapter 10, Azure and Excel - Machine Learning in the Cloud.
2. cabin and fare, pclass and fare, home.dest and fare are some examples.
3. Missing values could be replaced by the mean value of the variable.
4. Any unbalance in the dataset is referred to as bias. This will affect the results of any machine learning model, since the model will find more examples of a given class or some tendency to a particular target value.
5. You can, for example, try to see some correlations between variables using scatter plots.