# Questions tagged [decision-theory]

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### Checking whether Brier score is a strictly proper scoring rule

I want to check whether Brier Score is a strictly proper scoring rule based on some definition I found here. Since the paper is behind a paywall, I provide the definition here: A scoring rule assigns ...
10 views

### Bayesian Decision making with a mixed effects model

Background A company runs an AB test in which the unit of randomization (the customer) can interact with the variant several times throughout the experiment. The outcome is a binomial random variable ...
77 views

### Decision tree: how you would expect the next split based on a set of variables?

I'm trying to understand the logic behind a question I was given during a mock test. Can somebody help me please? I am not sure I can understand the concept, hence be able to make it right in a ...
195 views

### Loss functions in statistical decision theory vs. machine learning?

I'm quite familiar with loss functions in machine learning, but am struggling to connect them to loss functions in statistical decision theory . In machine learning, a loss function is usually only ...
14 views

### Is the admissible minimax decision rule ever a randomized action in frequentist statistics?

Are randomized action as opposed to pure action ever an admissible minimax rule in frequentist statistics,
25 views

### Why we use squared probabilities in the gini impurity

Why we are using squared probabilities instead of normal probabilities in gini impurity . Probabilities will always be positive , so why to square those ? Any leads would be highly apriciated , ...
16 views

### Statistical literature on task prioritisation problems

I am lookig for statistical papers on task prioritisation problems. In particular I am looking for solutions to the following problem or slight variations thereof: You have a set of tasks, each with a ...
26 views

### How do decision trees in random forests handle conflicts?

Let's say our input elements (training data) are 6 people with three attributes, Height, Weight, and Gender, and we are predicting if that person will have cancer or not (boolean 0 or 1). Let's say we ...
29 views

### Explain Dempster Shafer Equation

I have a question about the Dempster Shafer theory application. I have four models where the output is of abstract level (crisp). I understand I have to use the confusion matrix (precision/recall) to ...
26 views

### How to quantify intangible costs for decision making

In many situations, decision-making requires weighing multiple losses. For example, you might determine the optimal threshold for a churn classification problem by comparing the cost of offering a ...
25 views

### Ordering list of items by two criteria

I have a list of items with two scores: scoreA and scoreB. To be more specific they represent the average of a list of accuracy scores and their maximum. Both of the scores range from 0 to 100%. I'm ...
76 views

### What is the best strategy for the simplified version of the multi-armed bandit?

Consider a simplified version of the multi-armed bandit problem, where: like in the standard multi-armed bandit: when you pull the lever of 1 bandit you win/lose some amount from that bandit ...
8 views

### Integrated AHP and Fuzzy logic for Supplier categorization

I am looking into a supplier classification problem. As I have a lot of vague and subjective criteria I am using Fuzzy Logic to classify suppliers on two dimensions. However not all criteria are ...
39 views

### How does Random Forest split?

Random forests or random decision forests are an ensemble learning method for classification, regression, and other tasks that operate by constructing a multitude of decision trees at training time ...
51 views

### Stochastic dominance and mean preserving spread

I need someones help on understanding the concepts of stochastic dominance and mean preserving spread. I have an exercise which could be used for explanation. Consider the following lotteries: L1 ={...
67 views

Why is it that AdaBoost uses decision stumps for the weak learners? It seems simpler to me to just use the weighted majority of the data points for the classification. Why shouldn't we do this?
54 views

### The proper way to compute the posterior distribution of a distribution

Suppose I am a Bayesian working with multi-level data, $j$ and $t$. I run a model using $t$ that calculates the posterior distribution of a parameter $\theta_j$ for each $j$, which I then use to ...
24 views

### Bayesian decision making

I have a real world problem which I have reformulated into a simpler problem which hopefully you can help me solve. Picture this, I have the option to build a factory next to a conservation park. The ...
12 views

### Decision making with respect to utility function

I am currently working on a small project targeted towards predicting survival times (red, green functions) of certain engine parts. The ultimate goal is to decide what part would be the best choice ...
36 views

### Why would a Bayesian want to maximize expectation? [closed]

A Frequentist interprets probability as an estimate of how frequent an event is giving that we can repeat the experiment many times. It is natural for them to try to maximize the expected utility ...
33 views

### Aren't multi-armed bandits basically the same things as the Von Neumann-Morgenstern utility theorem?

I can't seem to find any material connecting the two ideas. How would one who is more knowledgeable about these topics relate them to one another? Is it that multi-armed bandits are just one way of ...
21 views

### Modeling and updating the reliability of two sources of information

I do not know the general framework this might fall under, apologies for the vague title. Assume that a decision maker's choice is dependent on two sources of information $f_1$ and $f_2$. Assume for ...
27 views

### Are the following terminologies error/risk/marmgin/regret bounds related?

I recently come across papers with titles resembling "Error/Risk/Margin/Regret Bounds" and I can't help but wondering if there is any fundamental (mathematical) difference between these terminologies? ...
49 views

### Optimal decisions based on frequentist estimators

Consider a decision problem aimed at minimizing the expected loss1 where the argument is a parameter estimate. In a Bayesian setting, given a posterior distribution of the parameter and the loss ...