Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dive into Decision Trees and Forests: A Theoretical Demonstration   Based on decision trees, many fields have arguably made tremendous progress
in recent years. In simple words, decision trees use the strategy of
"divide-and-conquer" to divide the complex problem on the dependency between
input features and labels into smaller ones. While decision trees have a long
history, recent advances have greatly improved their performance in
computational advertising, recommender system, information retrieval, etc. We
introduce common tree-based models (e.g., Bayesian CART, Bayesian regression
splines) and training techniques (e.g., mixed integer programming, alternating
optimization, gradient descent). Along the way, we highlight probabilistic
characteristics of tree-based models and explain their practical and
theoretical benefits. Except machine learning and data mining, we try to show
theoretical advances on tree-based models from other fields such as statistics
and operation research. We list the reproducible resource at the end of each
method.

10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat