Exploring learning outcomes, communication, anxiety, and motivation in learning communities: a systematic review Article Open access 24 November 2023 References Witherby, A. E. & Tauber, S. K. The current status of students’ note-taking: why and how do students take notes? J. Appl. Res...
Causal SVM "We present a new machine learning approach to estimate whether a treatment has an effect on an individual, in the setting of the classical potential outcomes framework with binary outcomes." DALEX "moDel Agnostic Language for Exploration and eXplanation." DALEXtra: Extension for 'DALEX...
In a two-player match I can represent this graphically as shown in the rightmost diagram in Figure 2. I cheated a bit in this notation by having the Boolean Player 1 Wins variable “somewhat” hatched. That’s because its value is observed during training, where the outcomes of the ...
The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the ...
Realism and presence in simulation: nursing student perceptions and learning outcomes. J Nurs Educ. 2019;58:330. Article Google Scholar Steigerwald SN, Park J, Hardy KM, Gillman LM, Vergis AS. Does laparoscopic simulation predict intraoperative performance? A comparison between the fundamentals of ...
The final step is to evaluate the predictive model’s performance against test data. There are essentially four outcomes for this binary classifier: Correctly labeled the value as malignant. Correctly labeled the value as benign. Incorrectly labeled the value as malignant....
Decision subjects: Counterfactual explanations can be used to explore actionable recourse for a person based on a decision received by a ML model. DiCE shows decision outcomes withactionablealternative profiles, to help people understand what they could have done to change their model outcome. ...
When using deep learning, we find, from a large amount of complex raw data, the deep interactions between features that are difficult to be expressed with traditional machines using artificial feature engineering. Related study outcomes include Wide & Deep, DeepFM, FNN, DCN, and other model...
The figure shows a tenfold cross-validation in the outer loop which is used to estimate the overall performance of the model by comparing the predicted outcomes for each student in the previously unseen test set with their actual outcomes. Within each of the 10 outer loops, a fivefold cross...
Provided by the Springer Nature SharedIt content-sharing initiative Subjects Human behaviour Medical research Outcomes research Psychology This article is cited by Individualized prediction models in ADHD: a systematic review and meta-regression Gonzalo Salazar de Pablo Raquel Iniesta Samuele Cortese Mol...