Essays about: "overfitting"

Showing result 1 - 5 of 62 essays containing the word overfitting.

  1. 1. Learning Policies for Path Selection in Attack Graphs

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Manuel Rickli; [2022]
    Keywords : ;

    Abstract : IT systems are indispensable nowadays. With thousands of hacking attempts happening daily, cyber defense mechanisms are crucial for maintaining a working state of those systems. Simulating an attacker is a means of preparing for future hacking attacks by determining the most likely vulnerabilities where an attack could be attempted. READ MORE

  2. 2. An Industrial Application of Semi-supervised techniques for automatic surface inspection of stainless steel. : Are pseudo-labeling and consistency regularization effective in a real industrial context?

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Mattia Zoffoli; [2022]
    Keywords : Deep Learning; Computer Vision; Semi-Supervised Learning; Automatic Inspection; Stainless Steel; Djupt lärande; datorseende; Semi-övervakat lärande; Automatisk inspektion; Rostfritt stål;

    Abstract : Recent developments in the field of Semi-Supervised Learning are working to avoid the bottleneck of data labeling. This can be achieved by leveraging unlabeled data to limit the amount of labeled data needed for training deep learning models. READ MORE

  3. 3. Credit Scoring using Machine Learning Approaches

    University essay from Mälardalens universitet/Akademin för utbildning, kultur och kommunikation

    Author : Bornvalue Chitambira; [2022]
    Keywords : Credit Scoring; Logistic Regression; Decision Trees; Artificial Neural Networks; Random forests; Support Vector Machine; k-nearest neighbour; cross validation; imbalanced dataset;

    Abstract : This project will explore machine learning approaches that are used in creditscoring. In this study we consider consumer credit scoring instead of corporatecredit scoring and our focus is on methods that are currently used in practiceby banks such as logistic regression and decision trees and also compare theirperformance against machine learning approaches such as support vector machines (SVM), neural networks and random forests. READ MORE

  4. 4. AUGMENTATION AND CLASSIFICATION OF TIME SERIES FOR FINDING ACL INJURIES

    University essay from Umeå universitet/Institutionen för datavetenskap

    Author : Marie-Louise Johansson; [2022]
    Keywords : computer science; machine learning; motion analysis; reconstructed ACL; anterior cruciate ligament; time series forest; dynamic time wapring; ACL; multivariate time series clasification; MTSC; time series classification; TSC; euclidean barycentric average; euclidean barycentric averaging; autmentation of time series; augmentation of multivariate time series; data augmentation; augmentation;

    Abstract : This thesis addresses the problem where we want to apply machine learning over a small data set of multivariate time series. A challenge when classifying data is when the data set is small and overfitting is at risk. Augmentation of small data sets might avoid overfitting. READ MORE

  5. 5. Combined Regularisation Techniques for Artificial Neural Networks

    University essay from Lunds universitet/Teoretisk partikelfysik; Lunds universitet/Institutionen för astronomi och teoretisk fysik; Lunds universitet/Beräkningsbiologi och biologisk fysik; Lunds universitet/Fysiska institutionen; Lunds universitet/Institutionen för teoretisk fysik

    Author : Joseph Binns; [2022]
    Keywords : Artificial Neural Networks; ANNs; Overfitting; Combined Regularisation Techniques; Regularisation Techniques; Regularisation; L2; Weight Decay; Dropout; Early Stopping; Physics and Astronomy;

    Abstract : Artificial neural networks are prone to overfitting – the process of learning details specific to a particular training data set. Success in preventing overfitting through combining the L2 and dropout regularisation techniques has led to the combination’s recent popularity. READ MORE