Sökning: "Backward elimination"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Backward elimination.

1. 1. The Effect of Online Advertising in a Digital World : Predicting Website Visits with Dynamic Regression

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Martin Björklund; Felix Hasselblad; [2021]
   Nyckelord :dynamic regression; prediction; forecasting; time series; machine learning; backward elimination; marketing; advertising;

   Sammanfattning : The goal of the thesis is to accurately predict future values of a company’s website visits and to estimate the uncertainty of those predictions. To achieve this, a dynamic regression model with an ARIMA error term is considered, using advertisement spending with lags and dummy variables for Black Friday and weekdays as predictors. LÄS MER

3. 2. Weight of evidence transformation in credit scoring models: How does it affect the discriminatory power?

   Magister-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Rickard Persson; [2021]
   Nyckelord :Credit Credit-scoring WOE weight of evidence Credit-scoring models; Mathematics and Statistics;

   Sammanfattning : Weight of evidence (WOE) transformation has been used for several decades in the credit industry. However, despite its widespread use, it has, surprisingly, been an overlooked approach in published literature. In this paper, we, therefore, investigate what effect WOE transformation has on the discriminatory power of a credit-scoring model. LÄS MER

4. 3. Comparing Variable Selection Algorithms On Logistic Regression – A Simulation

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :KEVIN SINGH; [2021]
   Nyckelord :Simulation-study; stepwise-regression; backward elimination; lasso-regression;

   Sammanfattning : When we try to understand why some schools perform worse than others, if Covid-19 has struck harder on some demographics or whether income correlates with increased happiness, we may turn to regression to better understand how these variables are correlated. To capture the true relationship between variables we may use variable selection methods in order to ensure that the variables which have an actual effect have been included in the model. LÄS MER

5. 4. Machine Learning-based Quality Prediction in the Froth Flotation Process of Mining : Master’s Degree Thesis in Microdata Analysis

   Master-uppsats, Högskolan Dalarna/Mikrodataanalys

   Författare :Eric Kwame Osei; [2019]
   Nyckelord :Froth Flotation; Machine Learning; Random Forest; Multiple Linear Regression; Artificial Neural Network;

   Sammanfattning : In the iron ore mining fraternity, in order to achieve the desired quality in the froth flotation processing plant, stakeholders rely on conventional laboratory test technique which usually takes more than two hours to ascertain the two variables of interest. Such a substantial dead time makes it difficult to put the inherent stochastic nature of the plant system in steady-state. LÄS MER

7. 5. Variable selection techniques for the Cox proportional hazardsmodel: A comparative study

   Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

   Författare :Simon Peterson; Klas Sehlstedt; [2018-03-08]
   Nyckelord :All subset selection; Backward elimination; Best subset selection; BeSS; Cox proportinal hazards model; least absolute shrinkage and selction operator; LASSO;

   Sammanfattning : In statistics different models are used to emulate real world processes. Variable selection refers to reduction of the number of parameters in the models in order to increase interpretability and model effectiveness. LÄS MER