Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Detection of Thin Boundaries between Different Types of Anomalies in
  Outlier Detection using Enhanced Neural Networks   Outlier detection has received special attention in various fields, mainly
for those dealing with machine learning and artificial intelligence. As strong
outliers, anomalies are divided into the point, contextual and collective
outliers. The most important challenges in outlier detection include the thin
boundary between the remote points and natural area, the tendency of new data
and noise to mimic the real data, unlabelled datasets and different definitions
for outliers in different applications. Considering the stated challenges, we
defined new types of anomalies called Collective Normal Anomaly and Collective
Point Anomaly in order to improve a much better detection of the thin boundary
between different types of anomalies. Basic domain-independent methods are
introduced to detect these defined anomalies in both unsupervised and
supervised datasets. The Multi-Layer Perceptron Neural Network is enhanced
using the Genetic Algorithm to detect newly defined anomalies with higher
precision so as to ensure a test error less than that calculated for the
conventional Multi-Layer Perceptron Neural Network. Experimental results on
benchmark datasets indicated reduced error of anomaly detection process in
comparison to baselines.

19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph