Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 29 for “"Confusion Matrix"”.
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Machine Learning for Predicting Prosthetic Limb Movements
… truth labels using classification accuracy and confusion matrix analysis.</p> <p>Experimental results demonstrate that the LSTM model effectively learns sequential patterns from the sEMG data with high accuracy. All exercises achieved at least 79.82% validation accuracy, and a F1-score of …
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The Effects of a Humanoid Robot's Non-lexical Vocalization on Emotion Recognition and Robot Perception
… the regular voice than from other sounds. The confusion matrix showed that happiness and sadness had the highest emotion recognition accuracy, which aligns with the previous research. Regular voice also induced higher trust, naturalness, and preference compared to other sounds. Interestingly, …
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Extensive Huffman-tree-based neural network for the imbalanced dataset and its application in accent recognition
… accuracy derived from hierarchical multiclass confusion matrix.
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Distances and Stability in Biological Network Theory
… improving over classical measures based on the confusion matrix, too coarse for this task. A combination of spectral and edit distances especially tailored for biological networks will be investigated and applied to several high-throughput biological datasets of different nature and with …
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Selecting the best model for predicting a term deposit product take-up in banking
… of the receiver operating characteristic curve, confusion matrix, GINI, kappa, sensitivity, specificity, and lift and gains charts. A multivariate adaptive regression splines model built on over-sampled data is found to be the best model for predicting term savings product takeup.
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Improving Model Generalization of Pneumonia Detection from Chest Xray Images Using Deep Learning and Transfer Learning
… accuracy (AUC 0.9573) on the external dataset. Confusion matrix analysis revealed that most errors occurred between Normal and Pneumonia classes, mirroring real world diagnostic challenges. In conclusion, DenseNet201 demonstrated superior robustness and generalization compared to ResNet152, …
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A developmental exploration of Chinese reading in a population of early readers: from eye movement control to textual coherence
… additional study is described where a character confusion matrix was generated that can be used as a resource for both pedagogical and psycholinguistic studies of Chinese reading and other studies interested in character recognition.
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An unsupervised approach to COVID-19 fake tweet detection
… MiniBatch K-Means, TF-IDF, Word2Vec, Bert, Confusion Matrix, Truncated SVD (Singular Value Decomposition), t-distributed stochastic neighbourhood embedding (t-SNE)
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An improved algorithm for iris classification by using support vector machine and binary random machine learning
… error rate (MER) were used by refers confusion matrix values output during data analysis for average and individual performance of each classifier. Besides that, Performance Visualization such as Stacked Bar Plot, Fourfold Plot, Receiver Operating Characteristic (ROC) Curve and …
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Metal culvert renewal prioritization framework development: A study for Saskatchewan Highways
… curve, percentage of correct predictions (PCP), confusion matrix, accuracy, precision, recall, and F1 score. The results of the study indicate that the artificial neural network optimized by genetic algorithm outperforms the other two methods, providing the most effective approach for culvert …
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Analysing the road reserve encroachment in Maseru Lesotho using remote sensing and image analysis
… have encroached on the road reserve. The confusion matrix was used to tell the best performing method and the results show that the indirect method, both in Qoaling and Maqalika performed best. All the methods showed that there was an encroachment on a road reserve, and found that …
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Machine learning approaches for malware classification based on hybrid artefacts
… accuracy, f1-score, Mean Absolute Error (MAE), confusion matrix, and Area under the ROC Curve (AUC). Combining two feature sets can provide the best classification performance on static file properties and dynamic analysis results, regardless of whether applying feature selection or not, …
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Network-Based Detection and Prevention System against DNS-Based Attacks
… We evaluated the two detection systems using a confusion matrix, including the recall, false-negatives rate, accuracy, and others. The detection system detects all case scenarios of the attacks while Snort missed 50% of the performed attacks. Based on the results, we can conclude that the …
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An intelligent system approach for predicting the risk of heart failure
… of the developed systems has been evaluated by a confusion matrix based on 221 datasets collected from a valid source. The obtained result demonstrates that the performance parameters of the FIS model provide superior results compared to the ANN model. The developed FIS system's accuracy, …
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BERT-Based Intrusion Detection System for RF Jamming Attacks in Vehicular Network
… in size, showed only moderate performance gains. Confusion matrix analysis revealed that all transformer models classified interfer- ence scenarios with near-perfect accuracy. However, distinguishing between smart and constant jamming attacks remained challenging, especially at lower speeds. …
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Quantifying Uncertainty in Model Evaluation
As Machine Learning models have quickly evolved in the past decade, ways of measuring their potential haven’t. This proposal will pose that simple point estimate performance indicators are ill suited to describe models that exhibit inherent variability. Addressing classifier performance variability …
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Classification of Foetal Distress and Hypoxia Using Machine Learning
… analysis, area under the curve plots, as well as confusion matrix. The simulation results indicate that machine learning classifiers provide good results in diagnosis of foetal hypoxia, in addition to acceptable results of different combinations of parameters to differentiate the cases.
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Speech perception in children with reading disabilities
… reading disabilities in two tasks: a Syllable Confusion Oddball task (SCO) and a Nonsense Syllable Confusion Matrix task (NSCM). The SCO task tested children’s ability to select a different syllable (either a consonant vowel–CV or vowel consonant–VC syllable) from a string of three such …
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Acoustic data optimisation for seabed mapping with visual and computational data mining
… were validated against ground truth data using a confusion matrix and kappa coefficients. For MBES, the classes derived from optimised data yielded better accuracy compared to that of the original data. For SBES, direct clustering was able to provide a relatively reliable overview of the …
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Investigating local ancestry inference models in mixed ancestry individual genomes
… measures borrowed from the machine learning confusion matrix. Finally, we noted that it may be more practical to extend existing models to incorporate more realistic biological assumptions. Hence, we propose a nonparametric hidden Markov model, that adjusts an existing model mSPECTRUM to …
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