[PDF] Top 20 A machine-learning approach to predict postprandial hypoglycemia
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A machine-learning approach to predict postprandial hypoglycemia
... that predict nocturnal hypoglycemia (for both single- and bi-hormonal AP systems) with high accu- racy, the prediction of postprandial hypoglycemia is still a challenge because of extreme ... See full document
13
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
22
Predicting Psychology Attributes of a Social Network User
... to predict the portrait of the person. The disad- vantage of this approach is that very often people do not write full information about themselves or knowingly indicate false information about ...use ... See full document
8
Characterising particulate random media from near-surface backscattering: A machine learning approach to predict particle size and concentration
... a machine learning approach that both the particle radius and concentration can be accurately measured when the boundary condition on the particles is of Dirichlet ...supervised machine ... See full document
8
Dependency Parsing by Inference over High recall Dependency Predictions
... two learning-based ap- proaches, we first describe a number of baselines, which provide simple reference scores giving some sense of the difficulty of each ...two machine learning systems: 1) an ap- ... See full document
5
FUZZY C-MEANS with APRIORI & ID3 for PREDICTING HEART STROKE RISK LEVEL
... efficient approach to predict heart stroke risk levels from the heart problem dataset by using machine learning ...Keywords: Machine learnin: Heart Problem: Fuzzy C-means: Apriori ... See full document
7
A Machine Learning Approach to Convert CCGbank to Penn Treebank
... In error analysis, the conversion F-measure of each kind of phrases is examined (see Figure 3). As for the F-measure of the top ten major kinds, seven of them are over 90%, two around 80% while the worst is 44.8%. The ... See full document
8
Proposing a Machine Learning Approach to Analyze and Predict Employment and its Factors
... Following the workflow outlined in the previous section, after filtering the desired variables, researchers cleaned all those variables which presents to much NaN (empty) values. In this case, the threshold used to ... See full document
7
<p>Reducing Opioid Prescriptions by Identifying Responders on Topical Analgesic Treatment Using an Individualized Medicine and Predictive Analytics Approach</p>
... of machine learning methods to train predictive models and this speci fi c category of algorithms is dif fi cult to interpret and understand because of their complex and non-linear ...explainable ... See full document
12
Machine Learning With Factor Scoring To Predict Diabetes Risk Level In Bangladesh
... where machine learning and data analysis applied to predict the diabetes risk level or used different machine learning approaches for classifying diabetes dataset by using different ... See full document
5
Predictive Migration for Application High Availability
... vector machine approach to predict failure events based on system log ...standard machine learning techniques such as Bayes networks, Hidden Markov Models (HMM), and Partially ... See full document
8
Internet-Sensor Information Mining Using Machine Learning Approach
... many machine learning methods, but often with a slightly different goal in ...hand, machine learning also employs data mining methods as "unsupervised learning" or as a ... See full document
7
A machine learning approach to predict perceptual decisions: an insight into face pareidolia
... While the perception of external sensory stimuli is a stimulus-dependent process, neuroimaging evidence of prestimulus activity suggests that it also depends on the brain states prior to the stimulus onset. However, ... See full document
16
A Machine Learning Approach to Predict Loan Default.
... Hailey Owen was born 16 June 1989 in Cleveland, Tennessee. She spent her entire childhood in Cleveland through her undergraduate education at Lee University. She began college with a love of math, but no career ... See full document
85
Optimum Crop Prediction using Data Mining and Machine Learning Techniques
... Abstract—In this paper, we develop a web based application system that will assist farmers in selecting the crop that is most suitable for his land. This system is better than other systems as it considers various ... See full document
5
Prediction Of Misclassification Data Based On Cognitive Computation Approach (CCA)
... Generally machine learning techniques are analysed in different categories in terms of predicting the incomplete values of large datasets, which propose outstanding performance or response from ... See full document
8
Sentence level quality estimation by predicting HTER as a multi component metric
... Despite not having conclusive results yet, we think that the idea is promising and that further experiments could have positive impact. Concern- ing the current development, several issues need to be further ... See full document
6
A Machine Learning Approach for Phenotype Name Recognition
... To evaluate the system, 10-fold cross validation has been used. Also the system has been tested using a separate test set. Table 2 gives the details of the results. The base system is our machine learning ... See full document
16
Theoretical Investigation on Artificial Intelligence: Classification and Aspects
... a machine with the ability to solve problems which are solved by natural human ...as learning and problem solving in machines which are solved by ... See full document
5
Predict the Price of Gold Based on Machine Learning Techniques
... In this paper, a solution based on machine learning was explored, which uses the combination of association rules algorithm Apriori and gray prediction model to reliably and effectively [r] ... See full document
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