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the use of electric classifier machine

Tissue Characterization With an Electrical Spectroscopy ...

2009-3-31  Abstract: This feasibility study introduces the use of a classifier based on electrical spectroscopy measurements for breast cancer tissue characterization. The classifier is of the support vector machine type, and the vector of data is made of electrical voltage measurements at 12 discrete electrical excitation frequencies over the beta dispersion range of the analyzed tissue and at discrete ...

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Machine Learning Classifiers. What is

2018-6-11  Evaluating a classifier. After training the model the most important part is to evaluate the classifier to verify its applicability. Holdout method. There are several

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External Validation of a Machine Learning Classifier to ...

2021-11-2  Unhealthy alcohol use (UAU) is one of the leading causes of global morbidity. A machine learning approach to alcohol screening could accelerate best practices when integrated into electronic health record (EHR) systems. This study aimed to validate externally a natural language processing (NLP) classifier developed at an independent medical center.

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Analysis and result of classification algorithm on email ...

Spam is the use of electronic messaging systems to send bulk data. In this paper, e-mail data were classified as ham email and spam email using supervised learning algorithms. Three different classifiers such as Naïve Bayesian (NB) classifier, K-nearest neighbor (KNN) classifier and Support Vector Machine (SVM) classifier were used.

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Non-intrusive load monitoring using artificial ...

2021-9-1  Among the techniques used for non-intrusive disaggregation of electric loads, the following can be highlighted: • Optimization algorithms [7,8];Artificial neural networks [9,10];Hidden Markov Chains [11,12]Support Vector Machines , , .. Despite recent advances considering NILM techniques , there is no standard in regards to a solution be used, considering the state of the art.

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The effective use of the one-class SVM classifier for ...

Bilal Hadjadji received the M.S. degree from the Faculty of Electronic andComputer Sciences, USTHB University, Algiers, Algeria, in 2012. Currently, he is a Ph.D. student at the same faculty. His research interests include machine learning, multiple classifiers system, and handwritten recognition.

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Discriminative Ridge Machine: A Classifier for High ...

2020-7-21  In this article, we introduce a discriminative ridge regression approach to supervised classification. It estimates a representation model while accounting for discriminativeness between classes, thereby enabling accurate derivation of categorical information. This new type of regression model extends the existing models, such as ridge, lasso, and group lasso, by explicitly incorporating ...

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RNAPosers: Machine Learning Classifiers for Ribonucleic ...

2020-12-28  Determining the three-dimensional (3D) structures of ribonucleic acid (RNA)–small molecule ligand complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA–small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used for pose prediction ...

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Machine Learning Classifier - Python

Machine Learning Classifier. Machine Learning Classifiers can be used to predict. Given example data (measurements), the algorithm can predict the class the data belongs to. Start with training data. Training data is fed to the classification algorithm. After training the classification algorithm (the fitting function), you can make predictions.

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COVID-Classifier: an automated machine learning model

2021-5-10  COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

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Tissue Characterization With an Electrical Spectroscopy ...

2009-3-31  Abstract: This feasibility study introduces the use of a classifier based on electrical spectroscopy measurements for breast cancer tissue characterization. The classifier is of the support vector machine type, and the vector of data is made of electrical voltage measurements at 12 discrete electrical excitation frequencies over the beta dispersion range of the analyzed tissue and at discrete ...

Read More
Machine Learning Classifier - Python

Machine Learning Classifier. Machine Learning Classifiers can be used to predict. Given example data (measurements), the algorithm can predict the class the data belongs to. Start with training data. Training data is fed to the classification algorithm. After training the classification algorithm (the fitting function), you can make predictions.

Read More
COVID-Classifier: an automated machine learning model

2021-5-10  COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

Read More
Discriminative Ridge Machine: A Classifier for High ...

2020-7-21  In this article, we introduce a discriminative ridge regression approach to supervised classification. It estimates a representation model while accounting for discriminativeness between classes, thereby enabling accurate derivation of categorical information. This new type of regression model extends the existing models, such as ridge, lasso, and group lasso, by explicitly incorporating ...

Read More
Use of a molecular classifier to identify usual ...

Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study Lancet Respir Med . 2019 Jun;7(6):487-496. doi: 10.1016/S2213-2600(19)30059-1.

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Implementation of Machine Learning Algorithms for

2021-5-4  Bengaluru, India. AbstractIn this paper, the implementation of Machine Learning algorithms, Random forest (RF), Support vector machine (SVM), and, Artificial neural networks (ANN), have been discussed. Today air pollution is one of the biggest environmental issues in the world. It poses a major threat to health and climate.

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RNAPosers: Machine Learning Classifiers for Ribonucleic ...

2020-12-28  Determining the three-dimensional (3D) structures of ribonucleic acid (RNA)–small molecule ligand complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA–small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used for pose prediction ...

Read More
(PDF) A Review of Machine Learning Algorithms

Machine learning algorithms automatically builds a clas- sifier by learning the characteristics of the categories from a set of classified documents, and then uses the clas-

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Cognitive Signal Classifier: improving the RF spectrum ...

2020-4-16  Cognitive Signal Classifier: improving the RF spectrum awareness. Improving the RF spectrum awareness is critical for Electronic Warfare (EW) applications. But overall it is at the basis of a more efficient spectrum sharing. This is important as more radios, communications systems, radars and many other applications, including internet-of ...

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Understanding Machine Learning: From Theory to

2016-4-13  Understanding Machine Learning Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a princi-pled way. The book provides an extensive theoretical account of the

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A machine learning classifier approach for identifying the ...

2021-10-24  Undernutrition is the main cause of child death in developing countries. This paper aimed to explore the efficacy of machine learning (ML) approaches in predicting under-five undernutrition in Ethiopian administrative zones and to identify the most important predictors. The study employed ML techniques using retrospective cross-sectional survey data from Ethiopia, a national-representative ...

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Machine Learning Classifier - Python

Machine Learning Classifier. Machine Learning Classifiers can be used to predict. Given example data (measurements), the algorithm can predict the class the data belongs to. Start with training data. Training data is fed to the classification algorithm. After training the classification algorithm (the fitting function), you can make predictions.

Read More
COVID-Classifier: an automated machine learning model

2021-5-10  COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

Read More
Use of a molecular classifier to identify usual ...

Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study Lancet Respir Med . 2019 Jun;7(6):487-496. doi: 10.1016/S2213-2600(19)30059-1.

Read More
Machine Learning Classifiers. What is

2018-6-11  Evaluating a classifier. After training the model the most important part is to evaluate the classifier to verify its applicability. Holdout method. There are several methods exists and the most common method is the holdout method. In this method,

Read More
Support Vector Machine (SVM) Based Classifier For

2014-10-30  Support vector machines are a type of classifier. They’re called machines because they generate a binary decision; they’re decision machines. Support vector machines try to maximize margin by solving a quadratic optimization problem [10]. Lagrange Multiplier is used in the optimization problem with following Quadratic Programming (3, 4, 5).

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Prediction of Sudden Cardiac Death Using Ensemble

2020-8-4  The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised machine learning methods have been successfully used for medical diagnosis. Ensemble classifiers are known to achieve better prediction accuracy than its constituent base classifiers.

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(PDF) A Review of Machine Learning Algorithms

Machine learning algorithms automatically builds a clas- sifier by learning the characteristics of the categories from a set of classified documents, and then uses the clas-

Read More
A simple burn wound severity assessment classifier based ...

Assessment of burn severity is critical for wound treatment. Spatial frequency domain imaging (SFDI) has been previously used to characterize burns based on the relationships between histology and tissue optical properties. Recently, multispectral and hyperspectral imaging optical features have been combined with machine learning to classify burn severity. Here, we investigated the use of SFDI ...

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svm-classifier GitHub Topics GitHub

2018-10-31  The Electric Network Frequency (ENF) is the supply frequency of power distribution networks, which can be captured by multimedia signals recorded near electrical activities. It normally fluctuates slightly over time from its nominal value of 50 Hz/60 Hz. The ENF remain consistent across the entire power grid.

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