[PDF] Top 20 Can Machine Learning Improve Recession Prediction Accuracy?
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Can Machine Learning Improve Recession Prediction Accuracy?
... utilize machine learning and statistical data mining tools in the economics/financial world with the goal of more accurately predicting ...Does machine learning and statistical data mining ... See full document
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Multi-step short-term power consumption forecasting with a hybrid deep learning strategy
... deep learning neural networks (DLNNs) became increasingly attractive throughout the world and were extensively employed in a large number of application fields, including natural language processing (NLP) [9], ... See full document
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Bridging a translational gap: using machine learning to improve the prediction of PTSD
... In a previous study [23], we evaluated the ability of ML-based feature-selection algorithm to extract one set of early risk indicators. We also compared various ML classification algorithms and evaluated predictability ... See full document
7
Explainable Recommendation through Attentive Multi-View Learning
... Multi-View Learning Model ...and improve accu- racy by optimizing key variables in the explainable structure ...To improve model accuracy, we propose an attentive multi-view learning ... See full document
8
A Cooperative Machine Learning Approach for Pedestrian Navigation in Indoor IoT
... length can be estimated rather accurately, heading evaluation is extremely problematic in indoor ...To improve the location accuracy, this paper proposes a cooperative system to estimate the ... See full document
20
Prediction of Onset Diabetes using Machine Learning Techniques
... Machine learning algorithms can help us to detect the onset ...diabetes can reduce patient’s health ...relatives can be benefited from the prediction’s ...various machine ... See full document
5
Robustness and prediction accuracy of machine learning for objective visual quality assessment
... the accuracy of the quality prediction is affected according to whether the noise is added to luminance, contrast or structure ...network can shed light on ...feature can be measured as the ... See full document
5
Can Machine Learning Algorithms Improve Phrase Selection in Hybrid Machine Translation?
... All tree-based alignments can be computed with a very high accuracy. However, due to the nature of statistical word alignment, the same does not hold for the alignment obtained from the SMT systems. If the ... See full document
6
Thyroid Prediction System using Machine Learning Techniques
... two machine earning algorithms: PCA and LDA and we will be comparing them using the classification models like Logistic regression, K-nearest neighbor, SVM, Naive Bayes, Decision tree and Random ...the ... See full document
8
Can Deep Learning Improve Genomic Prediction of Complex Human Traits?
... the prediction of com- plex traits in multiple ...in machine learning enable the implementation of high- dimensional regressions using nonlinear methods that have been shown to be effective in ... See full document
11
Blood pressure estimation from photoplethysmogram and electrocardiogram signals using machine learning
... two machine learning models, the Lasso regression and the ...pressure prediction work reported in ...features can indeed improve the performance of blood pressure ... See full document
7
Neural Network Ensemble for the Prediction Of Pathological Complete Response After Neoadjuvant Chemotherapy for Breast Cancer
... various machine learning algorithms are trained after pre-processing the data to check the performance of ...the accuracy of the proposed framework, ten evaluation metrics are calculated and ... See full document
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Dynamic selection of environmental variables to improve the prediction of aphid phenology: A machine learning approach
... Patron: Her Majesty The Queen Rothamsted Research Harpenden, Herts, AL5 2JQ.. Telephone: +44 (0)1582 763133 Web: http://www.rothamsted.ac.uk/.[r] ... See full document
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Dynamic selection of environmental variables to improve the prediction of aphid phenology : a machine learning approach
... White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/127857/ Version: Accepted Version Article: Holloway, Paul, Kudenko, Daniel orcid.org/0000-0003-3359-3255 and[r] ... See full document
22
Machine Learning Prediction and Classification
... Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly ...programmed. ... See full document
5
The P2P Risk Assessment Model Based on the Improved AdaBoost SVM Algorithm
... of learning machine, P2P risks can be ...rithm can improve the risk platform classification ...classification can be controlled in ... See full document
9
Thyroid Prediction System using Machine Learning Techniques
... Disease diagnosis involves analyzing symptoms and detecting whether a disease persists in a body, but analyzing symptoms itself is a complex task. Providing disease diagnosis at early stages with higher accuracy ... See full document
8
Prediction of Rainfall using Simplified Deep Learning based Extreme Learning Machines
... Abstract. Prediction of rainfall is needed by every farmer to determine the planting period or for an institution, eg agriculture ministry in the form of plant ...the accuracy of predicted results from BMKG ... See full document
12
Prediction of Parkinson Disease by Best Accuracy using Supervised Classification Machine Learning Approach
... A classifier that categorizes the data set by setting an optimal hyper plane between data. I chose this classifier as it is incredibly versatile in the number of different kernelling functions that can be applied ... See full document
5
Cancer Prediction and Prognosis Using Machine Learning Techniques
... various machine learning techniques for different type of cancer prediction and prognosis (Breast Cancer, Lung Cancer, ...own accuracy and the key point in using different machine ... See full document
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