A Comparative Analysis of Different Algorithms in Machine Learning Techniques for UnderwaterAcoustic Signal Recognitiondoi:10.1007/978-981-19-3311-0_34Speech recognition is a process of capturing and changing the speech into digitized sound waves, from which it converts to basic language or phonemes...
Some machine learning algorithms are described as “supervised” machine learning algorithms as they are designed for supervised machine learning problems. Popular examples include:decision trees,support vector machines, and many more. Our goal is to find a useful approximation f(x) to the function f...
All useful machine learning algorithms will have some variance, and some of the most effective algorithms will have a high variance. Algorithms with a high variance often require more training data than those algorithms with less variance. This is intuitive if we consider the model approximating a ...
However, the research about a comparison of different machine learning methods is rare; particularly, a comparison of the NN, Extreme Gradient Boosting (XGBoost3), and Light Gradient Boosting Machine (LightGBM4) lacks. A study about the latter two machine learning algorithms in petroleum engineering...
and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you’ll become well versed in techniqu...
This, in turn, would require the neural network to "remember" previously encountered information and factor that into future calculations. And the problem of remembering goes beyond videos: For example, manynatural language understandingalgorithms typically deal only with text, but need to recall infor...
Learning algorithms Machine Learning Optimization Stochastic Learning and Adaptive Control System Robustness 1 Introduction Single hidden layer feedforward neural network (SLFNs) [1] is one of the classic methods used in data analysis, due to its powerful nonlinear mapping capability. However, it...
Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction Svetlana Illarionova Dmitrii Shadrin Evgeny Burnaev Scientific Reports (2025) Decreasing dynamic predictability of global agricultural drought with warming climate Haijiang Wu Xiaoling Su Xiaotao Hu ...
However, uncertainties regarding machine learning outcomes represents one of the main problems with machine learning algorithms (Yang et al., 2020). There are three main sources of uncertainty in machine learning studies including data quality, the sample of data collected from the domain, and model...
:musical_note: Algorithms written in different programming languages - https://zoranpandovski.github.io/al-go-rithms/ - ZoranPandovski/al-go-rithms