Predicting MIS-performance Using Learning Curves
Predicting Students’ Performance Using Machine Learning Techniques
... A decision tree model represents a tree structure that is similar to a flowchart. In this structure, each internal node represents a test on a dataset attribute while each tree branch represents the test outcome. In ...
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Predicting Application Performance using Supervised Learning on Communication Features
... in performance for the best mapping in comparison to the worst mapping (note the logarithmic scale on the y- ...the performance variations from mapping are statistically insignificant: 8- and 512-byte re- ...
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Predicting players’ performance in the game of cricket using machine learning
... players’ performance as the entire ...career performance and then his recent ...players’ performance for their models to predict outcomes of IPL ...venue, performance features of the two ...
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Predicting Students’ Performance by Learning Analytics
... academic performance. We consider test performance as well as social and physiological factors to determine the key features that affect student ...works using the same data ...
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Learning Pulse: a machine learning approach for predicting performance in self-regulated learning using multimodal data
... as figure 6 shows, the software is running on two server in- frastructures: the Cloud and the Virtual Machine. Not re- ported here are the controllers of the Third Party Sensors and the Learner Dashboard as the System ...
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Using learning curves to mine student models
... the performance of each individual constraint over ...average performance of the constraint set as a whole over time, for which a learning curve can then be ...the learning curve for the ...
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The possibility of predicting learning performance using features of note taking activities and instructions in a blended learning environment
... evaluated using multiple regression analysis and a step wise method of selecting ...contents using mainly a textbook, and so the number of terms pre- sented was ...
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Predicting motor learning performance from Electroencephalographic data
... In the following, we investigate whether TTT can be pre- dicted on a trial-to-trial basis from EEG recorded in the upcoming target’s planning or baseline phase. To do so, we separated the data into group-wise (ideally) ...
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Predicting Academic Performance via Machine Learning Methods
... methods using Naïve Bayes Classifier and Random Forest algorithm for developing machine learning models, which can functionally predict the grades for ECEN ...
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Predicting Pilot Success Using Machine Learning
... This thesis uses the same data most recently used for demographic analysis of both attrition and performance. In that recent study, Meyer [2] used statistical hypothesis testing to find categorical biases between ...
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Predicting network performance in IoTenvironments using LSTM
... of using traditional machine learning models to predict round trip times, so one of the main research questions for this thesis was to find out if the predicting accuracy would increase when ...
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Predicting Academic Performance of Students from VLE Big Data using Deep Learning Models
... student performance, are ...their performance, implying that students living in the rural areas may have hindrances or connectivity issues in accessing the VLE and hence the negative association with their ...
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Predicting supply chain risks using machine learning: The trade-off between performance and interpretability
... by predicting their occurrence and mitigating their adverse ...machine learning techniques and their applicability in supply chain risk ...prediction performance and neglect the importance of ...
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Learning Curves of Harvester Operators
... of using historical logging docu- ments is that there is no influence of the observer as in time ...overall performance to some degree but the ten- dency can be ...
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NETPerfTrace – Predicting Internet Path Dynamics and Performance with Machine Learning
... of predicting Internet path changes and path performance using traceroute measurements and machine lear- ning ...and performance degradation, therefore the relevance of the pro- ...and ...
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Predicting performance of non-contiguous I/O with machine learning
... It is very difficult for users to estimate how an I/O pattern will perform under a given set of optimization parameters; they therefore typically try various parameters, which resembles a limited brute force approach. ...
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Predicting the performance of business partners, using issue data of the iSense system : mapping a perception to data using machine learning
... partner performance information from the iSense ...machine learning with a continuous ...reduced using principle component analysis in order to fit on the sparse ...
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Predicting Theropod Hunting Tactics using Machine Learning
... Currently, due to the advancements in technology, a scientist can capture more considerable amounts of data from monitoring animals that includes the animal's movements, social interactions, vocalizations, and even their ...
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Predicting Computing Prices Dynamically Using Machine Learning
... Each computing device that implements the machine-learned model or other aspects of the present disclosure can include a number of hardware components that enable performance of the techniques described herein. ...
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Predicting mortgage demand using machine learning techniques
... the performance of the models, we can already see differences between the ...compared using the characteristics described in Table 6. Using a 95% significance level, there appears to be a significant ...
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