Comparative Study of Different Orange Data Mining Tool-Based AI Techniques in Image Classification
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[1] Forrest N. Iandola,et al. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.
[2] Blaz Zupan,et al. Orange: Data Mining Fruitful and Fun - A Historical Perspective , 2013, Informatica.
[3] David R. Karger,et al. Tackling the Poor Assumptions of Naive Bayes Text Classifiers , 2003, ICML.
[4] Gongzhu Hu,et al. Predicting the characteristics of people living in the South USA using logistic regression and decision tree , 2011, 2011 9th IEEE International Conference on Industrial Informatics.
[5] Devashree Vaishnav,et al. Comparison of Machine Learning Algorithms and Fruit Classification using Orange Data Mining Tool , 2018, 2018 3rd International Conference on Inventive Computation Technologies (ICICT).
[6] Subhashree Mohapatra,et al. Artificial Intelligence for Smart Healthcare Management: Brief Study , 2020 .
[7] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[8] Devavrat Shah,et al. Explaining the Success of Nearest Neighbor Methods in Prediction , 2018, Found. Trends Mach. Learn..
[9] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[10] Han Liu,et al. Decision tree learning based feature evaluation and selection for image classification , 2017, 2017 International Conference on Machine Learning and Cybernetics (ICMLC).
[11] R Muthukrishnan,et al. LASSO: A feature selection technique in predictive modeling for machine learning , 2016, 2016 IEEE International Conference on Advances in Computer Applications (ICACA).
[12] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Sander M. Bohte,et al. Editorial: Artificial Neural Networks as Models of Neural Information Processing , 2017, Front. Comput. Neurosci..