Questions tagged [monte-carlo]

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Which Model for predicting flight delays is appropriate except Random Forest and Decision Tree? (Monte Carlo?)

Im studying M.Sc Data Science and in the module "Decision Support Systems" me and my group have to make a presentation. Our Proposal is the following: Background With generally high demand ...
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Confusion regarding which distribution Monte Carlo considers for sampling

Considering Bayesian posterior inference, which distribution does Monte Carlo sampling take samples from: posterior or prior? Posterior is intractable because the denominator (evidence) is an ...
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Action-value estimation of deterministic policies with Monte Carlo method

In Monte Carlo-based action value estimation problem for a deterministic policy (estimation of $q_{\pi}(s,a)$),the estimation problem seems not to be well-defined because $q_{\pi}(s,a)$ by ...
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20 views

How to perform a Monte Carlo simulation with continuous sampling using discrete quantiles?

Assume I have registered the duration of 10 tasks and built the table below with using this data: Duration For how many tasks it happened 4 days 5 task 6 days 2 task 8 days 2 task 10 days 1 task ...
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1 vote
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36 views

Monte Carlo Markov Chain

I was trying to figure out what is a Monte Carlo Markov Chain. From what I understand it is a way of computing an approximation of a probability distribution, which cannot compute exactly. So we ...
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27 views

How do I find the optimal dropout rate for Monte Carlo Dropout?

I have a text classifier with 3 dropout layers. I tried to use Monte Carlo Dropout (MCD) technique to improve its performance, however its performance hasn't improved. MCD improved performance when ...
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33 views

How to resolve IndexError while doing Monte Carlo for 1000 runs? [closed]

Below code runs without any problem, however when I run the same code using Monte Carlo Analysis for 1000 runs, it gives IndexError. Can someone explain why this happens. Thanks ...
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18 views

Is it a good idea to use the mean and standard deviation of coefficients from other models as my prior in Bayesian Regression?

I have a dataset that I’ve been playing around with for school I have gotten very good results with a bunch of methods (Ridge, Lasso, ElasticNet, SVM, Bagging, Stacking and NN even) Now I’m having a ...
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0 answers
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MCMC algorithm -- understanding some paremeters

I am trying to understand an MCMC program. I manage to run it, but I am trying to understand the meaning of the some parameters in the analysis. The code is something like this ...
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  • 113
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1 answer
25 views

What is the most common practice of generating (X,Y) from an arbitrary CDF or PDF?

So I can generate X from arbitrary CDF F(x) by the procedure above. Can it be generalized to two variables? How, exactly? If not, what's the best way to generate <...
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0 votes
1 answer
91 views

Pull Random Numbers from my Data (Python)

Let's imagine I have a series of numbers that represents cash flows into some account over the past 30 days in some time window. This data is non-normal but it does represent some distribution. I ...
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1 vote
0 answers
24 views

How can I build a simulation environment that assess different risk policies? [closed]

I work in fin-tech and would like to build some sort of simulation program to assess how different inputs will impact net revenue. For example, if we create new policies based on ML scores, how would ...
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Test data for statistical t-test in Python

first of all sorry if this is not the proper place to ask but i have been trying to create some dummy variables in order to run a students t-test as well as a welch t-test and then run a monte-carlo ...
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1 vote
1 answer
161 views

Having a reward structure which gives high positive rewards compared to the negative rewards

I am training an RL agent using PPO algorithm for a control problem. The objective of the agent is to maintain temperature in a room. It is an episodic task with episode length of 9 hrs and step size(...
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  • 515
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1 answer
84 views

How to handle differences between training and deploying of an RL agent

Hi I am training an RL agent for a control problem. The objective of the agent is to maintain temperature in a zone. It is an episodic task with episode length of 10 hrs and actions being taken every ...
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  • 515
1 vote
1 answer
619 views

Different results every time I train a reinforcement learning agent

I am training an RL agent for a control problem using PPO algorithm. I am using stable-baselines library for it. The objective of an agent is to maintain a temperature of 24 deg in a zone and it ...
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  • 515
3 votes
1 answer
4k views

Evaluating a trained Reinforcement Learning Agent?

I am new to reinforcement learning agent training. I have read about PPO algorithm and used stable baselines library to train an agent using PPO. So my question here is how do I evaluate a trained RL ...
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0 answers
22 views

Best Method for Data Analysis on a 100 numerical IVs and 200 numerical DVs

I think I might need the help of this valuable community for a task. I have been given a dataset for 100 numerical independent variables (IVs) that predict output for 200 numerical values (from monte ...
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1 vote
1 answer
138 views

How to formulate reward of an rl agent with two objectives

I have started learning reinforcement learning and trying to apply it for my use case. I am developing an rl agent which can maintain temperature at a particular value, and minimize the energy ...
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  • 515
2 votes
1 answer
247 views

MCMC for finding Bayesian Neural Network

Is someone familiar with such an approach: Suppose I want to build a bayesian neural network, with distributions over my parameters instead of point estimates. First I train my network with standard ...
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5 votes
1 answer
192 views

Estimating the value of $\pi$ with a Monte Carlo dartboard: $<$ or $\leq$?

I'm trying to figure out which is the proper way to estimate $\pi$ using the Monte Carlo method randomly distributing points in a square that also contains an inscribed circle. Some sources say to ...
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1 vote
1 answer
50 views

What is the intuition behind using Monte Carlo to solve a differential equation

Conceptually, I understand how a numerical method like Monte Carlo is used to solve a definite integral. Because integral of a function is the area bounded by the curve, the ratio of random points ...
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1 vote
1 answer
101 views

Evaluating value functions in RL

I'm working my way through the book Reinforcement Learning by Richar S. Sutton and Andrew G. Barto and I am stuck on the following question. The value of a state depends on the the values of the ...
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  • 179
18 votes
1 answer
15k views

What is Monte Carlo dropout?

I understand how to use MC dropout from this answer, but I don't understand how MC dropout works, what its purpose is, and how it differs from normal dropout.
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  • 495
1 vote
1 answer
136 views

Why not use max(returns) instead of average(returns) in off-policy Monte Carlo control?

As I understand it, in reinforcement learning, off-policy Monte Carlo control is when the state-action value function $Q(s,a)$ is estimated as a weighted average of the observed returns. However, in ...
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1 vote
1 answer
32 views

In first visit monte carlo are we assuming the environment is the same over episodes?

Watching this video (11:30) that presents the simplest algorithm for reinforcement learning: Monte Carlo Policy Evaluation, which says in general: The first time a sate is visited: increment N(s): N(...
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1 vote
1 answer
332 views

How is Importance-Sampling Used in Off-Policy Monte Carlo Prediction?

In the section, "Off-Policy Prediction via Importance Sampling", found in the chapter on monte carlo methods of the second edition of Sutton and Barto's, "Reinforcement Learning: An Introduction", the ...
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1 vote
0 answers
218 views

How to use pymc3 to sample the mean of a Pareto random variable?

I Have a variable which is Pareto-ly distributed 'x', with unknown alpha and m. I want to find out the distribution of its mean, so I use the following model: ...
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  • 11
-1 votes
1 answer
999 views

Parameter estimation for a model with multiple input parameters

So I've this model that simulates an ecosystem and outputs its attributes, like its chemistry, temperature etc. There are lots of input parameters to the model. My job is to write a program to figure ...
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4 votes
1 answer
1k views

What visualization I should choose for Monte Carlo simulations in timeline events?

I wasn't sure if I should open this question in Cross Validated or here. But since the question belongs to a bigger project related with Data Science, I chose this one. I will present a simplified ...
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