Some widely known classifiers will also be included in the comparison: regular perceptron, extreme learning machine regularized via weight decay (ELM-reg), MLP and also the SVM, which has been recently shown notably effective and represents the state-of-art. Besides, the Hebbian perceptron will ...
Thus, using the KELM learning framework can eliminate the variations in optimization constraints in the Support Vector Machine (SVM) and Least Squares Support Vector Machine (LSSVM). Because of its optimization restrictions, KELM exhibits an improved generalization performance compared with SVM and LSSV...
python acnet/acb.py ACNet v2 (Diverse Branch Block, DBB):Diverse Branch Block: Building a Convolution as an Inception-like Unit. DBB (CVPR 2021)is a CNN component with higher performance than ACB and still no inference-time costs. Sometimes I call it ACNet v2 because "DBB" is 2 bits la...
extreme speed on both small and large data sets, Bindings forR,Python,MATLAB / Octave,Java, andSpark, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, ...
The kernel trick allows us to employ high-dimensional feature space for a machine learning task without explicitly storing features. Recently, the idea of utilizing quantum systems for computing kernel functions using interference has been demonstrated e
The battery RUL prediction process based on the dual GPR model and indirect HI is shown in Fig.5. The model implementation is based on Python and leverages relevant machine learning libraries, most notably the GPy library. GPy allows for the flexible construction and optimization of Gaussian proce...
computer vision & machine learning https://github.com/wanttobeno/sod compress https://github.com/wanttobeno/snappy Dongle https://github.com/wanttobeno/Dongle spy++ https://github.com/wjx0912/MySpy Shell Extension for Windows Explorer https://github.com/abhimanyusirohi/ThumbFish (nice...
Li, W., et al.: Local binary patterns and extreme learning machine for hyperspectral imagery classification. IEEE Trans. Geosci. Rem. Sens. 53(7), 3681–3693 (2015). https://doi.org/10.1109/tgrs.2014.2381602 8. Ghamisi, P., Dalla Mura, M., Benediktsson, J.A.: A survey on spectral...
2.2. Kernel Extreme Learning Machine KELM is a new variant of the well-regraded extreme learning machine (ELM) developed for the first time by Huang et al. [56]. The KELM integrates the kernel function with the structure of ELM to guarantee that the resulting network can reveal an acceptabl...
Kernel extreme learning machineParameter optimizationFruit fly optimizationBankruptcy predictionSlime mould algorithmLevy flightBankruptcy prediction is a crucial application in financial fields to aid in accurate decision making for business enterprises. Many models may stagnate to low-accuracy results due to ...