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 19 of 19 for “"Kaggle"”.
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Decoding team performance in a self-organizing collaboration network using community structure
… team performance in the self-organizing Kaggle platform and find that my methodology can achieve an average accuracy of 57% when predicting the result of a competition while using no performance information to identify communities. First, I motivate our interest in team performance and …
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Towards an automatic predictive question formulation
… to describe all 54 prediction problems on the Kaggle data science competition website[14] and so is comprehensive. The implemented system consists of a web application connected to a server-side interpreter, which translates input from the web application into a series of transformation and …
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CLASSIFICATION OF IMAGES BASED ON PIXELS THAT REPRESENT A SMALL PART OF THE SCENE. A CASE APPLIED TO MICROANEURYSMS IN FUNDUS RETINA IMAGES
… pixels. These models were trained using the Kaggle and Messidor datasets and tested independently against the Kaggle dataset, showing a sensitivity of 95\% and 91\%, a specificity of 98\% and 93\%, and an area under the Receiver Operating Characteristics curve of 0.98 and 0.96, respectively, …
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Applying Artificial Intelligence and Mobile Technologies to Enable Practical Screening for Diabetic Retinopathy
… to create a generalized model, I used a public Kaggle database or approximately 35,000 retina images and applied a transfer learning approach using the Inception v3 architecture, to build a convolutional neural net (CNN) model that predicts referable DR. As expected, the performance of the …
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MakeML : automated machine learning from data to predictions
… problem on the public data science platform Kaggle.
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A Deep Learning Based Pipeline for Image Grading of Diabetic Retinopathy
… images, as evidenced by scores for both the Kaggle dataset and the IDRiD dataset.
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Credit scorecards in retail banking: enhancing interpretability through shapley values and evaluating the effectiveness of alternative data for improved accuracy
… the highest area under the curve on the Kaggle home credit data.
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Improving Computational Efficiency of MRI Brain Tumour Analysis Using Hybrid Machine Learning Models
… and non-tumor cases using a dataset sourced from Kaggle. After preprocessing, the dataset was analyzed using Support Vector Machines (SVM), VGG-19, and YOLOv10 models. Metrics including accuracy, precision, recall, F1-score, and ROC-AUC were utilized to evaluate the model's effectiveness. The …
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Predicting an Economic Recession Using Machine Learning Techniques
… available data from the online open source Kaggle, which provided ordinal categorical data for the specific data utilized. The major findings of this study were that the ML algorithm RF performed better at recession prediction than its rival ANN. Due to the fact that two ML algorithms in …
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Análisis de la Encuesta de Salud Nacional y Examen de Nutrición de Estados Unidos (NHANES) usando machine learning
En este trabajo se usará el conjunto de datos de kaggle National Health and Nutrition Examination Survey. La finalidad será diseñar e implementar diferentes modelos no supervisados para identificar patrones, descubrir como tienden los datos a agruparse y si existen comorbilidades entre las …
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A Machine Learning Approach to Predicting the Onset of Type II Diabetes in a Sample of Pima Indian Women
… Women Diabetes dataset was downloaded from the Kaggle website. Different experiments were conducted on the dataset. Each</em><em> </em>machine learning algorithm was trained on unscaled data using a balanced and unbalanced dataset and again using scaled data with a balanced and unbalanced …
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Lietuvių kalbos teksto atpažinimas /
… were synthetically generated because the found “Kaggle A-Z" dataset did not have them. Also, an additional set of photos of Lithuanian words has been created to test already trained models. Four different neural network models were trained and tested. Their results were compared with Tesseract …
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Classifying advanced malware into families based on instruction link analysis
… performs on a publicly available dataset on Kaggle and GitHub. The experimental data gave supportive validation of the proposed feature selection model by Gaussian Mixer Model in R environment.
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
… Knowledge Extraction Evolutionary Learning and Kaggle dataset. The simulation results show that the highest improvement of H-BFGS in terms of generalisation accuracy is on the Voice Gender classification with 43.33% improvement for 60:40 data division. While H-DFP, the highest improvement …
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Enhancing E-commerce Dataset recommendations using BERT and Named Entity Recognition
… Tested on over 4,373 metadata entries from Kaggle and Google Dataset Search, EDMRec consistently delivers more relevant, context-aware recommendations, demonstrating its capability to support more insightful analysis and data-driven decision-making in e-commerce datasets.
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Application of Machine Learning Techniques for the Classification of Lower Back Pain in Human Body
… Original dataset is taken from website named Kaggle (https://www.kaggle.com/). This dataset is normalized first and then an Automatic Feature Engineering technique has been implemented on the dataset to extract the most important features to do the correct classification. Training of each …
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A Comparative Analysis of Machine Learning Models and Traditional Statistical Models for Continuous-Time Survival Analysis
… failure clinical records dataset obtained from Kaggle. A rigorous statistical framework was employed, utilizing 100 iterations of stratified train-test splits to generate robust performance distributions. Distributional assumptions were systematically tested using Shapiro-Wilk and Levene’s tests …
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A Machine Learning Classifiers Approach for Cardiovascular Disease Diagnosis
… of overfitting. In this Thesis the dataset from Kaggle on Cardiovascular Disease (CVD) diagnosis and Python tools on Anaconda platform were used. The data was cleaned, and 5 feature reduction techniques were investigated. Here, in addition a statistical unbiased ensemble feature reduction is …
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Automatizované testování a vyhodnocování modelů hlubokých neuronových sítí na vestavěných platformách
Táto magisterská práca sa zameriava na automatizované testovanie modelov hlbokých neurónových sietí na vstavaných platformách. Teoretická časť práce skúma populárne úložiská modelov umelej inteligencie a nástroje na získavanie modelov z takýchto úložísk. Teoretický základ práce taktiež zahŕňa …