Questions tagged [estimators]

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Subtraction of two variances (scores)

I was wondering, would it be correct to say, when we treat two variances of two populations as a random variable itself (or as a score), that we can simply get a resultant variance V_subtract = V_pop1 ...
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-1 votes
2 answers
97 views

gridsearchcv best coefficients do not match well with the perfect line

I wrote a program to find the best combination of coefficients to describe a variable. However, the coefficients from the gridsearchcv do not match well with the expected line. This is a sample of my ...
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2 votes
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Offline/Batch Reinforcement Learning: Doubly Robust Off-policy Estimator takes huge values

Context: My team and I are working on a RL problem for a specific application. We have data collected from user interactions (states, actions, etc.). It is too costly for us to emulate agents. We ...
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2 answers
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What is the value of AIC criterion if RSS is 0? [closed]

The AIC formula is : $AIC = 2k + n Log(RSS/n)$ So if RSS is equal to 0, it is undefined. How do I deal with this? What value should it take?
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1 vote
1 answer
114 views

Pearson correlation coefficient - is correlation estimator acceptable?

As far as I know when it comes to theory, we use Pearson correlation when we want to check the correlation between two variables, which are both continuous or discrete. For a mixed case it's not so ...
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2 votes
2 answers
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How can I do the correlation between two estimators?

I'm working with several estimators of all kind. Then, I want to stack these estimators, and the best is if they have low correlation between them. I suppose that the correlation method depends on ...
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  • 131
1 vote
1 answer
230 views

Math behind, MSE = bias^2 + variance

Based on the deeplearningbook: $$MSE = E[(\theta_m^{-} - \theta)^2]$$ $$equals$$ $$Bias(\theta_m^{-})^2 + Var(\theta_m^{-})$$ where m is the number of samples ...
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-1 votes
1 answer
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Is it possible to estimate

For example, if I want to know a page views/relative prevalence of a Reddit post, and I have the upvote and downvote data. Is it valid that I use the upvote and downvote to predict that, even if I ...
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Observation Operator - Data Assimilation

In data assimilation, one assumes the existence of a observation operator $\mathcal{H}$ that maps the model-state vector $\bf{x_b}$ to $ \bf{y_b}$ (the model-equivalent of the observations $\bf{y_o}$) ...
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6 votes
1 answer
2k views

What is the difference between a Categorical Column and a Dense Column?

In Tensorflow, there are 9 different feature columns, arranged into three groups: categorical, dense and hybrid. From reading the guide, I understand categorical columns are used to represent ...
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2 answers
104 views

Latent variables with thresholds

There are many ML techniques to estimate latent variables such as the EM algorithm. Is there a technique that allows for thresholds for each of the latent variables? I have a feature space with 10 ...
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3 votes
3 answers
236 views

Using recurrent neural networks for modeling errors in IMUs

Inertial measurement units (IMU), usually composed of accelerometers and gyroscopes; are well known to have inherent errors in their data, originating from bias, random walk noise, temperature ...
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1 vote
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3k views

How to Save TensorFlow model using estimator.export_savemodel() [closed]

How can i Save the TensorFlow model using estimator.export_savedmode() ? Especially, what should i put inside the ...
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4 votes
1 answer
33k views

'DecisionTreeClassifier' object has no attribute 'importances_'

I've this code in order to visualize the most important feature of each model: ...
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1 vote
0 answers
69 views

Plotting estimates of Tail Dependence Coefficient in R

I want to plot the following estimate of the tail dependence coefficient: $\hat{\lambda}_n=\frac{1}{k}\sum_{j=1}^nI_{\{X_j>X_{(n-k)},Y_j>X_{(n-k)}\}}$ where $I_{(.)}$ is an indicator function ...
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Estimating forward velocity for a swimmer

With a modern IMU with 9 angles of freedom collecting accelerometer, magnetometer and gyroscope data on 3 axis, what would be the best approach on filtering the data and handling it to accurately ...
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5 votes
1 answer
2k views

How to estimate the mutual information numerically?

Suppose I have a sample {$z_i$}$_{i\in[0,N]}$ = {($x_i,y_i$)}$_{i\in[0,N]}$ which commes from a probability distribution $p_z(z)$. How can I use it to estimate the mutual information between X and Y ? ...
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