Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Autostacker: A Compositional Evolutionary Learning System   We introduce an automatic machine learning (AutoML) modeling architecture
called Autostacker, which combines an innovative hierarchical stacking
architecture and an Evolutionary Algorithm (EA) to perform efficient parameter
search. Neither prior domain knowledge about the data nor feature preprocessing
is needed. Using EA, Autostacker quickly evolves candidate pipelines with high
predictive accuracy. These pipelines can be used as is or as a starting point
for human experts to build on. Autostacker finds innovative combinations and
structures of machine learning models, rather than selecting a single model and
optimizing its hyperparameters. Compared with other AutoML systems on fifteen
datasets, Autostacker achieves state-of-art or competitive performance both in
terms of test accuracy and time cost.

9
The categories of this paper are: nlin
19
The categories of this paper are: eess
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th