Essays about: "lasso regularization"
Showing result 1 - 5 of 16 essays containing the words lasso regularization.
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1. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
University essay from Lunds universitet/Statistiska institutionenAbstract : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. READ MORE
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2. Explainable Machine Learning in Cardiovascular Diagnostics
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. READ MORE
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3. Predicting misuse of subscription tranquilizers : A comparasion of regularized logistic regression, Adaptive Bossting and support vector machines
University essay from Uppsala universitet/Statistiska institutionenAbstract : Tranquilizer misuse is a behavior associated with substance use disorder. As of now there is only one published article that includes a predictive model on misuse of subscription tranquilizers. READ MORE
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4. Modeling Organic Installs in a Free-to-Play Game
University essay from KTH/Matematisk statistikAbstract : The Free-To-Play industry relies on getting a huge inflow of new players that might result in future gross bookings. Consequently, getting organic new players is crucial to ensure its health, especially as they have no direct associated acquisition cost. READ MORE
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5. Predicting Subprime Customers' Probability of Default Using Transaction and Debt Data from NPLs
University essay from KTH/Matematisk statistikAbstract : This thesis aims to predict the probability of default (PD) of non-performing loan (NPL) customers using transaction and debt data, as a part of developing credit scoring model for Hoist Finance. Many NPL customers face financial exclusion due to default and therefore are considered as bad customers. READ MORE
