Sökning: "causal discovery"

Visar resultat 6 - 10 av 14 uppsatser innehållade orden causal discovery.

1. 6. Interactive Visual Exploration of Causal Structures for Neuropathic Pain Diagnosis

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Yuwen Hu; [2021]
   Nyckelord :Causal structures; causality visualization; neuropathic pain; discomfort drawing; healthcare; interactive technologies.;

   Sammanfattning : Revealing causal structures from observational data is an essential task in many data analysis issues across various domains, such as natural sciences, business, and healthcare. In healthcare, neuropathic pain is one of the most common medical problems, whose diagnosis process has well-understood causal structures. LÄS MER

3. 7. Causal Discovery Algorithms for Context-Specific Models

   Master-uppsats, KTH/Matematisk statistik

   Författare :Mohamed Nazaal Ibrahim; [2021]
   Nyckelord :Causality; Causal Discovery; Statistics; Kausalitet; Kausal Upptäckt; Statistik;

   Sammanfattning : Despite having a philosophical grounding from empiricism that spans some centuries, the algorithmization of causal discovery started only a few decades ago. This formalization of studying causal relationships relies on connections between graphs and probability distributions. LÄS MER

4. 8. Which firm characteristics determine access to finance for SMEs within the East African Community?

   Kandidat-uppsats,

   Författare :Joseph Fridner; Emil Jonsson; [2020-06-29]
   Nyckelord :SME; access to finance; East African Community; sub-Saharan Africa; logit; FDR; asymmetric information;

   Sammanfattning : Financial constraints among SMEs are generally more prevalent in the developing world than in the developed world, but SMEs in sub-Saharan Africa stand out as being particularly constrained. Previous studies also show causal links between access to finance and company growth and increased prosperity. LÄS MER

5. 9. Variable Selection for Estimating Optimal Sequential Treatment Decisions Using Bayesian Networks

   Master-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Joel Persson; [2020]
   Nyckelord :decision theory; causal inference; variable selection; graphical models; causal discovery; dynamic treatment regimes; dynamic programming; reinforcement learning; observational study; Mathematics and Statistics;

   Sammanfattning : We propose a variable selection method for estimating decision rules of optimal sequential treatment assignments when the decision-relevant variables are unknown. Standard variable selection methods are insufficient in this setting since they choose covariates that are predictive of the outcome, not those that interact with the treatment on the outcome and are therefore relevant for decision-making. LÄS MER

7. 10. Causal discovery in the presence of missing data

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Ruibo Tu; [2018]
   Nyckelord :causal discovery; missing data; PC;

   Sammanfattning : Missing data are ubiquitous in many domains such as healthcare. Depending on how they are missing, the (conditional) independence relations in the observed data may be different from those for the complete data generated by the underlying causal process (which are not fully observable) and, as a consequence, simply applying existing causal discovery methods to the observed data may give wrong conclusions. LÄS MER