Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comparative Study of Instance Based Learning and Back Propagation for
  Classification Problems   The paper presents a comparative study of the performance of Back Propagation
and Instance Based Learning Algorithm for classification tasks. The study is
carried out by a series of experiments will all possible combinations of
parameter values for the algorithms under evaluation. The algorithm's
classification accuracy is compared over a range of datasets and measurements
like Cross Validation, Kappa Statistics, Root Mean Squared Value and True
Positive vs False Positive rate have been used to evaluate their performance.
Along with performance comparison, techniques of handling missing values have
also been compared that include Mean or Mode replacement and Multiple
Imputation. The results showed that parameter adjustment plays vital role in
improving an algorithm's accuracy and therefore, Back Propagation has shown
better results as compared to Instance Based Learning. Furthermore, the problem
of missing values was better handled by Multiple imputation method, however,
not suitable for less amount of data.

34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc