Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [parameter-estimation]

58 questions
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2 answers

Parameterization regression of rotation angle

Let's say I have a top-down picture of an arrow, and I want to predict the angle this arrow makes. This would be between $0$ and $360$ degrees, or between $0$ and $2\pi$. The problem is that this target is circular, $0$ and $360$ degrees are exactly…
Jan van der Vegt
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CNN memory consumption

I'd like to be able to estimate whether a proposed model is small enough to be trained on a GPU with a given amount of memory If I have a simple CNN architecture like this: Input: 50x50x3 C1: 32 3x3 kernels, with padding (I guess in reality theyre…
Simon
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Which one first: algorithm benchmarking, feature selection, parameter tuning?

When trying to do e.g. a classification, my approach currently is to try out various algorithm first and benchmark them perform feature selection on the best algorithm from 1 above tune the parameters using the selected features and…
Ricky
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Knn distance plot for determining eps of DBSCAN

I would like to use the knn distance plot to be able to figure out which eps value should I choose for the DBSCAN algorithm. Based on this page: The idea is to calculate, the average of the distances of every point to its k nearest neighbors. …
Marc Lamberti
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Gibbs sampling in R

I have the following model: $y_{it}=\alpha + x'_{it}\beta_{i} + \epsilon_{it}, \text{ } i=1,2,...,N, \text{ } t=1,2,...,T$ (1) $\beta_{i}= z'_{i}\gamma+\eta_{i}$ (2) with $\epsilon_{it} \sim N(0,\sigma_{\epsilon_{i}}^{2})$ and $\eta_{i} \sim…
quant
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Why Huber loss has its form?

Huber loss formula is $\hspace{3.0cm} L_\delta(a) = \begin{cases} \frac{1}{2} a^2 && |a| \leq \delta \\ \delta (|a| - \frac{1}{2} \delta) && |a| > \delta\end{cases}$ where $a = y - f(x)$ As I read on Wikipedia, the motivation of Huber loss is to…
HOANG GIANG
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How to tune weights in Voting Classifier (Sklearn)

I am trying to do the following: vc = VotingClassifier(estimators=[('gbc', GradientBoostingClassifier()), ('rf', RandomForestClassifier()), ('svc', SVC(probability=True))], …
Abhinav Gupta
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Can Expectation Maximization estimate truth and confusion matrix from multiple noisy sources?

Suppose we have $m$ sources, each of which noisily observe the same set of $n$ independent events from the outcome set $\{A,B,C\}$. Each source has a confusion matrix, for example for source $i$: $$C_i = \begin{bmatrix} 0.98 & 0.01 & 0.07 \\ 0.01 &…
Brendan Hill
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generalized likelihood ratio test (GLRT)

I am having trouble in understanding the generalized likelihood ratio test (GLRT). Can anyone explain what it is to me, or point me toward an easy-to-understand reference? Is it a supervised or unsupervised method? How GLRT relates to Bayesian…
Arkan
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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 positive parameters $\alpha$, $\beta$, $\delta$,…
MuhammedYunus StopTheGenocide
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Artificial Neural Networks and Efficient Parameter Optimization

I have a bunch of test measurements data and a semi-empirical model that has 18 parameters which I have to find so that the model fits my data well. So far I've managed to find and optimise the parameters using Optimisation and Global Optimisation…
Lior
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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 parameters (feature coefficients in the linear regression…
NAS_2339
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How to estimate the lambda e to reweighing translation probabilities of entries in a dictionary

In this paper, Brown et al. proposed the usage of dictionary entries in addition to the machine translation probabilities that we're used to in the Math of Statistical Machine Translation. He describes: We formalize an intuitive account of…
alvas
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predict parameters of linear function

My questions seems very trivial, but I can't quite grasp it. I am also aware this post asks for opinions and knowhow, but do not know were else to ask. I do have quite a lot of experience solving even somewhat difficult machine learning problems,…
Tom S
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How to get the maximum likelihood estimate of the categorical distribution parameters using Lagrange optimization?

Let's say our data is discrete-valued and belongs to one of $K$ classes. The underlying probability distribution is assumed to be a categorical/multinoulli distribution given as $p(\textbf{x}) = \prod_{k = 1}^{K}\mu_{k}^{x_{k}}$ where x is a one-hot…
Shashank Kumar
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