Page 57 - Fister jr., Iztok, and Andrej Brodnik (eds.). StuCoSReC. Proceedings of the 2018 5th Student Computer Science Research Conference. Koper: University of Primorska Press, 2018
P. 57
Research, 0711.2914, 2007.
[9] Juan J. Rodr Guez and Carlos J. Alonso. Boosting
Interval-Based Literals: Variable Length and Early
Classification. Series in Machine Perception and
Artificial Intelligence, 57:149–171, 2002.
[10] G. Guo, H. Wang, D. Bell, Y. Bi, and K. Greer. KNN
Model-Based Approach in Classification. On The
Move to Meaningful Internet Systems 2003: CoopIS,
DOA, and ODBASE, pages 986–996, 2003.
[11] E. M. Kamel, M. Wafy, H. M. Ibrahim, and I. A.
Badr. Comparison of different classification algorithms
for certain weed seeds’ species and wheat grains
identification based on morphological parameters.
IJCSI International Journal of Computer Science
Issues, 12(5):110–116, 2015.
[12] G. Oreˇski and S. Oreˇski. An experimental comparison
of classification algorithm performances for highly
imbalanced datasets. Central European Conference on
Information and Intelligent, pages 4–11, 2014.
[13] M. Richardson. Principal Component Analysis. 2009.
[14] R. Rifkin and A. Klautau. In Defense of One-Vs-All
Classification. Journal of Machine Learning Research,
5:101–141, 2004.
[15] D. Srivastava and L. Bhambhu. Data Classification
using support vector machine. Journal of Theoretical
and Applied Information Technology, 12(1), 2005.
[16] Michele A. Trovero and Michael J. Leonard. Time
Series Feature Extraction. 2018.
[17] J. Wang, P. Liu, M. F. H. She, S. Nahavandi, and
A. Kouzani. Bag-of-words representation for
biomedical time series classification. Biomedical Signal
Processing and Control, 8(6):634–644, 2013.
[18] W. Yang, L. Xu, X. Chen, F. Zheng, and Y. Liu.
Chi-Squared Distance Metric Learning for Histogram
Data. Mathematical Problems in Engineering,
2015:1–12, 2015.
StuCoSReC Proceedings of the 2018 5th Student Computer Science Research Conference 59
Ljubljana, Slovenia, 9 October
[9] Juan J. Rodr Guez and Carlos J. Alonso. Boosting
Interval-Based Literals: Variable Length and Early
Classification. Series in Machine Perception and
Artificial Intelligence, 57:149–171, 2002.
[10] G. Guo, H. Wang, D. Bell, Y. Bi, and K. Greer. KNN
Model-Based Approach in Classification. On The
Move to Meaningful Internet Systems 2003: CoopIS,
DOA, and ODBASE, pages 986–996, 2003.
[11] E. M. Kamel, M. Wafy, H. M. Ibrahim, and I. A.
Badr. Comparison of different classification algorithms
for certain weed seeds’ species and wheat grains
identification based on morphological parameters.
IJCSI International Journal of Computer Science
Issues, 12(5):110–116, 2015.
[12] G. Oreˇski and S. Oreˇski. An experimental comparison
of classification algorithm performances for highly
imbalanced datasets. Central European Conference on
Information and Intelligent, pages 4–11, 2014.
[13] M. Richardson. Principal Component Analysis. 2009.
[14] R. Rifkin and A. Klautau. In Defense of One-Vs-All
Classification. Journal of Machine Learning Research,
5:101–141, 2004.
[15] D. Srivastava and L. Bhambhu. Data Classification
using support vector machine. Journal of Theoretical
and Applied Information Technology, 12(1), 2005.
[16] Michele A. Trovero and Michael J. Leonard. Time
Series Feature Extraction. 2018.
[17] J. Wang, P. Liu, M. F. H. She, S. Nahavandi, and
A. Kouzani. Bag-of-words representation for
biomedical time series classification. Biomedical Signal
Processing and Control, 8(6):634–644, 2013.
[18] W. Yang, L. Xu, X. Chen, F. Zheng, and Y. Liu.
Chi-Squared Distance Metric Learning for Histogram
Data. Mathematical Problems in Engineering,
2015:1–12, 2015.
StuCoSReC Proceedings of the 2018 5th Student Computer Science Research Conference 59
Ljubljana, Slovenia, 9 October
