Essays about: "variable selection methods"
Showing result 1 - 5 of 55 essays containing the words variable selection methods.
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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. Assessment and evaluation of heterogeneity in data from immune infiltration spatial niches in lung cancer
University essay from Lunds universitet/Matematisk statistikAbstract : The protein biomarker expressions in three types of sampled immune INFILTration spatial niches in lung cancer tissue were measured using the new technology Digital Spatial Profiler (DSP). The three types of immune INFILTration that were observed in lung tumors were STROMA identified as immune cells separate from tumor cells, Tertiary lymphoid structures (TLS) identified as dense structures of organized immune cells and finally Infiltraterate where immune cells dispersed among and in direct contact with tumor cells (INFILT). READ MORE
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3. A Dual-Lens Approach to Loss Given Default Estimation: Traditional Methods and Variable Analysis
University essay from KTH/Matematik (Avd.)Abstract : This report seeks to thoroughly examine different approaches to estimating Loss Given Default through a comparison of traditional estimation methods, as well as a deeper variable analysis on micro, small, and medium-sized companies using primarily regression decision trees. The comparative study concluded that estimating loss given default depends heavily on business-specific factors and data variety. READ MORE
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4. Capturing time variation within systemic risk estimation
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : Systemic risk can be defined as the risk to the whole financial system. Financial institutions may contribute more or less to this risk, and measuring the systemic risk contributions of institutions is of central importance for regulators. READ MORE
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5. Predicting Airbnb Prices in European Cities Using Machine Learning
University essay from Blekinge Tekniska Högskola/Fakulteten för datavetenskaperAbstract : Background: Machine learning is a field of computer science that focuses on creating models that can predict patterns and relations among data. In this thesis, we use machine learning to predict Airbnb prices in various European cities to help the hosts in setting reasonable prices for their properties. READ MORE