Questions tagged [parameter-estimation]
The parameter-estimation tag has no summary.
58 questions
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Estimating Final Vehicle Counts from Pairwise Marginals Using Python
I am working with vehicle registration data from website
. The website provides counts for various combinations of vehicle attributes such as Maker, RTO, Fuel, Category, SubCategory, and Emission.
...
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Dynamic parameter estimation of coupled ODE on time-series data using ML methods
I have a coupled ODE that represents time-series data that I found using SINDy. Using machine learning methods, I want to estimate the coupled ODE coefficients in real time using my data and do a ...
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How to train a model to estimate the coefficients of a coupled ODE?
Consider the coupled ODE system below (Lotka-Volterra equations):
$$
\frac{dx}{dt} = \alpha x - \beta x y, \\
\frac{dy}{dt} = - \gamma y + \delta x y ,
$$
How can I train a model to estimate the ...
- 4,372
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Given the total cost of a graph walk, how to estimate the cost of each edge?
I have a real-world problem in which I have a collection of nodes and their edges. This collection is composed of hundreds of nodes and thousands of connections. Then I have about 10 K datapoints each ...
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Is there anyway to evaluate the estimation results of least square
Consider the scenario where a practical problem is tackled utilizing the method of least squares. Upon each iteration, an estimation of the parameter $\theta$ is derived via $\hat{\theta} = (X^\top X)^...
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1
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Optimizing decision tree
I have a question regarding the technique/technology which could be applied for the issue:
Suppose I have a rule-based tree or decision tree which predicts a variable Y based on variables A,B,C. This ...
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2
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Is probabilities mean of predicted class (RandomForest) a consistent estimator of class recall?
I'm working on a classification problem in order to predict among 50 different classes.
I'm using a Random Forest classifier and I'm using the predict_proba method ...
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2
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2
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Depth Estimation Algorithms without Reference Image in Computer Vision for Webcam Captured Video Data of a Person
I am currently working on a computer vision project that involves analyzing video data of a person captured from a webcam. In this project, I need to compute the depth map or distance of a specific ...
- 121
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Learning additional parameters that are not weights of a neural network
In addition to training the weights of a neural network, I also want to optimize other parameters (that are constant but satisfy some conditions over the entire data set). As an example, one can ...
- 101
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Is number of Parameters a sufficient benchmark for measuring how much resource the end model will use?
I want to do a platform-free benchmark for some custom ML models. Calculating the elapsed time during making predictions from certain size data is not suitable since I am constantly using different ...
- 188
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Using scipy.minimize to find the maximum likelihood estimates for multivariate gaussian
Let's say I have a 100x2 normally distributed array of data.
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How are parameters selected in cross-validation?
Suppose I'm training a linear regression model using k-fold cross-validation. I'm training K times each time with a different training and test data set. So each time I train, I get different ...
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Verifying my understanding of MLE & Gradient Descent in Logistic Regression
Here is my understanding of the relation between MLE & Gradient Descent in Logistic Regression. Please correct me if I'm wrong:
1) MLE estimates optimal parameters by taking the partial derivative ...
- 367
2
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3
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367
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Why should MLE be considered in Logistic Regression when it cannot give a definite solution?
If MLE (Maximum Likelihood Estimation) cannot give a proper closed-form solution for the parameters in Logistic Regression, why is this method discussed so much? Why not just stick to Gradient Descent ...
- 367
3
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The fine line dividing ML modelling and statistical modelling
I've been thinking about the difference between ML modelling and statistical modelling.
I would to ask, on a philosophical level, is my thinking correct: modelling is basically a process of fitting a ...
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