Krahasoni metodat

	CNN e zgjeruar	XGBoost
Fusha	Mësimi i thellë	Mësimi i makinës
Familja	Machine learning	Machine learning
Viti i origjinës	2016	2016
Krijuesi	van den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.	Chen, T. & Guestrin, C.
Lloji	Deep learning (dilated 1D convolutional network)	Ensemble (gradient-boosted decision trees)
Burimi themelues	van den Oord, A. et al. (2016). WaveNet: A Generative Model for Raw Audio. arXiv.	Chen, T. & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD, 785–794.
Emërtime të tjera	Dilate Edilmiş CNN (WaveNet / TCN), WaveNet, Temporal Convolutional Network, TCN	XGBoost, extreme gradient boosting, scalable tree boosting
Të lidhura	5	5
Përmbledhja	A Dilated CNN is a one-dimensional convolutional network whose receptive field grows exponentially with depth, letting it model long-range structure in time series and audio signals. WaveNet (van den Oord et al., 2016) and the Temporal Convolutional Network of Bai, Kolter and Koltun (2018) are the prominent members of this family.	XGBoost (Extreme Gradient Boosting) is a scalable tree-boosting algorithm introduced by Tianqi Chen and Carlos Guestrin in 2016. It builds a strong predictor by adding decision trees one at a time, each correcting the errors left by the trees before it, and is a powerful prediction method widely used in competitions.