Linear and logistic regressions make predictions about numbers, but we also need
algorithms to classify instances of data in a certain class, ie, to label the instance as …

In times of big data tree-based algorithms are an important method of machine learning
which supports decision making, eg, in medicine, finance, public policy and many more …

To fully understand how this algorithm works, we can look at a simplified run through for the
first loop. First, we select the best attribute, a, from the set of attributes A. Based on the …

Machine learning has become a hot topics in the past few years. The challenge of generic
classification is akin to the problem of medical diagnosis. On a case or an object …

Abstract Classification and Regression Trees (CARTs) are off-the-shelf techniques in
modern Statistics and Machine Learning. CARTs are traditionally built by means of a greedy …

In Chapter 4, we looked at the process of building a decision tree. Decision trees can overfit
on top of the data in some cases—for example, when there are outliers in the data. Having …

A classification or regression treecan be used to depict adecision tree, which is a prediction
model. One of the oldest and most essential methods is the classification and regression …

Tree methods are some of the best and most commonly used methods in the field of
statistical learning. They are widely used in classification and regression modeling. This …

This master thesis is devoted to Classification and Regression Trees (CART). CART is
classification method which uses historical data to construct decision trees. Depending on …

This chapter describes about the classification methods for data mining. The method
involves the construction of a decision tree, a collection of decision nodes, connected by …