Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient and Accurate In-Database Machine Learning with SQL Code
  Generation in Python   Following an analysis of the advantages of SQL-based Machine Learning (ML)
and a short literature survey of the field, we describe a novel method for
In-Database Machine Learning (IDBML). We contribute a process for SQL-code
generation in Python using template macros in Jinja2 as well as the prototype
implementation of the process. We describe our implementation of the process to
compute multidimensional histogram (MDH) probability estimation in SQL. For
this, we contribute and implement a novel discretization method called equal
quantized rank binning (EQRB) and equal-width binning (EWB). Based on this, we
provide data gathered in a benchmarking experiment for the quantitative
empirical evaluation of our method and system using the Covertype dataset. We
measured accuracy and computation time and compared it to Scikit Learn state of
the art classification algorithms. Using EWB, our multidimensional probability
estimation was the fastest of all tested algorithms, while being only 1-2% less
accurate than the best state of the art methods found (decision trees and
random forests). Our method was significantly more accurate than Naive Bayes,
which assumes independent one-dimensional probabilities and/or densities. Also,
our method was significantly more accurate and faster than logistic regression.
This motivates for further research in accuracy improvement and in IDBML with
SQL code generation for big data and larger-than-memory datasets.

0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th