204.674 hasil untuk machine learning
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Artikel Jurnal
Single trajectory characterization via machine learning
…and limited localization precision. In this paper, we propose a machine learning method based on a random forest architecture, which is able to associate single trajectories to the underlying diffusion mechanism with high accuracy. In addition, the algorithm is able to determine the anomalous…
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ACL2(ml): Machine-Learning for ACL2
ACL2(ml) is an extension for the Emacs interface of ACL2. This tool uses machine-learning to help the ACL2 user during the proof-development. Namely, ACL2(ml) gives hints to the user in the form of families of similar theorems, and generates auxiliary lemmas automatically. In this paper, we present…
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SUPERVISED MACHINE LEARNING APPROACHES: A SURVEY
One of the core objectives of machine learning is to instruct computers to use data or past experience to solve a given problem. A good number of successful applications of machine learning exist already, including classifier to be trained on email messages to learn in order to distinguish between…
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Machine learning for biomedical literature triage.
This paper presents a machine learning system for supporting the first task of the biological literature manual curation process, called triage. We compare the performance of various classification models, by experimenting with dataset sampling factors and a set of features, as well as three…
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Artikel Jurnal
Machine Learning Aided Electronic Warfare System
In this article, a machine learning aided electronic warfare (EW) system is presented and the simulation results are discussed. The developed EW system uses an automatic decision tree generator to create engagement protocol and a fuzzy logic model to quantify threat levels. A long-short term memory…
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Artikel Jurnal
Application of Machine Learning in Microbiology
…of high-throughput sequencing technology. To deal with this problem, machine learning (ML) methods have been widely applied to the field of microbiology. Literature reviews have shown that ML can be used in many aspects of microbiology research, especially classification problems, and for exploring…
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Machine learning for advanced energy materials
…become necessary. The latest advancements in artificial intelligence and machine learning have therefore increased the expectation that data-driven materials science would revolutionize scientific discoveries towards providing new paradigms for the development of energy materials. Furthermore, the…
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Artikel Jurnal
R.ROSETTA: an interpretable machine learning framework
Abstract Background Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing…
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Artikel Jurnal
Machine Learning for Predicting Students’ Employability
…the reasons. To predict students' employability before graduation, machine learning models were employed. These include logistic regression; decision tree, random forest, and an unsupervised clustering (K-Means) algorithm. This research, therefore, aims to predict the full-time employability of…
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Artikel Jurnal Teks lengkap
An Industry-Ready Machine Learning Ontology
This article presents an industry-ready ontology for the machine learning domain, which is named “ML Ontology”. While based on lightweight modelling languages, ML ontology provides novel features including built-in queries and quality assurance, as well as sophisticated reasoning. With ca. 700…
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Machine learning capabilities in headache diagnosis
…as it can independently recognize and even classify headaches using machine learning. Research objective: Review of scientific literature and summary of current machine learning capabilities in headache diagnosis Materials and Methods: A literature review was conducted using PubMed and Google…
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Machine Learning at the Atomic Scale
Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condensed-phase systems. This short review…
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Artikel Jurnal
Novel jet observables from machine learning
Abstract Previous studies have demonstrated the utility and applicability of machine learning techniques to jet physics. In this paper, we construct new observables for the discrimination of jets from different originating particles exclusively from information identified by the machine. The…
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Sentiment Analysis Using Machine Learning Approach
…between four text classification algorithms - Naïve Bayes, Support Vector Machine, Decision Tree and Random Forest, using different feature extraction techniques, such as Bag of words and TF-IDF. In addition, the models are evaluated using accuracy, precision, recall and F-score metrics. Our…
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Constraining Fission Yields Using Machine Learning
…these observables as well. In this work, we exploit Monte Carlo and machine learning techniques to reproduce mass and kinetic energy yields, for phenomenological models and in a model-free way. We begin with the spontaneous fission of 252Cf, where there is abundant experimental data, to validate…
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MACHINE LEARNING FOR APPROXIMATING UNKNOWN FACE
…problem of facial approximation based on skull digital 3D model with deep learning techniques. The skull 3D models used for appearance reconstruction are generated by the original photogrammetric system in automated mode. These 3D models are then used as input for the algorithm for face appearance…
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Ensuring social distancing using machine learning
COVID-19 (Coronavirus) has affected our daily life and is slackening the global economy. In this fight against the COVID-19, social-distancing is proving to be an effective measure to slow down the transmission of coronavirus. In order to control the spread of transmission of COVID-19, social…
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Artikel Jurnal
Quantum machine learning beyond kernel methods
Comparing the capabilities of different quantum machine learning protocols is difficult. Here, the authors show that different learning models based on parametrized quantum circuits can all be seen as quantum linear models, thus driving general conclusions on their resource requirements and…
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Applications of Machine Learning at BESIII
BESIII is an experiment at the high precision frontier of hadron physics in τ-charm region. Machine learning techniques have been used to improve the performance of BESIII software. In this proceeding, we present novel approaches with XGBoost for multi-dimensional distribution reweighting, muon…
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Artikel Jurnal
Machine Learning in Antibacterial Drug Design
…traditional approaches in medicinal chemistry. In particular, machine learning is gaining importance with the growth of the available data collections. One of the critical areas where this methodology can be successfully applied is in the development of new antibacterial agents. The latter is…
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