# Questions tagged [statistical-ai]

For questions about the applications/clarifications/intuitions/proofs behind the use of statistical methods in AI/ML programs.

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### In logistic regression, do I try to fit the graph perfectly or mimimize the error in the predicted probabilities?

In linear regression, I train the model so the graph runs best through the data points, so the geometric distance between f(x) and $y^i$ is minimized. Now, is it correct that in logistic regression I ...
1 vote
39 views

### How can we construct a skewed noise distribution using the maximum likelihood approach?

When the probability of observing a large positive error is larger than the probability of observing a large negative error in binary classification, how can this be modelled by a skewed noise ...
21 views

1 vote
73 views

### What would be the reason behind using plots (such as box-plots or histograms) for ML development?

I've been learning Python machine-learning using this project report and the guy who wrote it begins by visualizing his data using various statistical analysis methods: histograms, density plots, box ...
1 vote
24 views

### Does distribution of data augmentation parameters matter?

Idea Let's say we have simple pictures dataset containing 40x40 images of digits. We have only one image of each digit. We want to use that as training set, but we need more data, so we use data ...
216 views

### Is the target assumed to be a noisy version of the output of the model in machine learning?

I wonder if the following equation (you can find it in almost every ML book) refers to a general assumption that we make when using machine learning: $$y = f(x)+\epsilon,$$ where $y$ is our output, $f$...
83 views

### Can AI be understood as a generalized statistics tool? [duplicate]

I am a (soon-to-become, to be honest) theoretical physicist. I want to learn a bit about AI. So as you know in physics we develop theories based on as few and as simple basic equations as possible ...
87 views

### When could a linear discriminant give excellent or possibly even the optimal classification accuracy?

I am actually reading the linear classification. There is a question in the question set behind the chapter in the book as follows: Sketch two multimodal distributions for which a linear discriminant ...
892 views

### What's going on in the equation of the variational lower bound?

I don't really understand what this equation is saying or what the purpose of the ELBO is. How does it help us find the true posterior distribution?
71 views

### Simplification of expected reward under the limit in continuous tasks

I was reading the average reward setting for continuous tasks from rich sutton's book (page 202, 2nd edition). There he perform a simplification over the expected reward under the limit approaching to ...
2k views

### Why do we need Upsampling and Downsampling in Progressive Growing of Gans

I was working recently on Progressive Growing of GANs (aka PGGANs). I have implemented the whole architecture, but the problem that was ticking my mind is that in simple GANs, like DCGAN, PIX2PIX, we ...
26 views

### Mapping given probabilities to empirical probabilities

Consider following problem statement: You have given $n$ actions. You can perform any of them. Each action gives you success with some probability. The challenge is to perform given finite number of ...
1 vote
70 views

### Is there any way to apply linear transformations on a vector other than matrix multiplication?

I am trying to optimize the cost function calculation in regression analysis using a non-matrix multiplication based approach. More specifically, I have a point $x = (1, 1, 2, 3)$, to which I want to ...
497 views

### What makes a machine learning algorithm a low variance one or a high variance one?

Some examples of low-variance machine learning algorithms include linear regression, linear discriminant analysis, and logistic regression. Examples of high-variance machine learning algorithms ...
125 views

### How to calculate the data noise variance for a prediction interval?

I have a neural network that connects $N$ input variables to $M$ output variables (qoi). By default, neural networks just give out point estimations. Now, I want to plot some of the quantity of ...
1 vote
39 views

### Do the variance and bias belong to the policy or value functions?

Recently, I read many papers on variance and bias. But I am still confused by the two notions, the variance or bias belongs to who? Policy or value? If the variance or bias is large or low, what ...
63 views

### Is maximum likelihood estimation meaningless for a dataset of only outliers?

From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution. I always interpreted it as the ...
98 views

### Is there a way of computing a prominence score based on the prevalence of features in an image?

Is there any previous work on computing some sort of prominence score based on the prevalence of features in an image? For example, let's say I am classifying images based on whether or not they have ...
1 vote
56 views

### What is the difference between an generalised estimating equation and a recurrent neural network?

What is the difference between a generalised estimating equation (GEE) model and a recurrent neural network (RNN) model, in terms of what these two models are doing? Apart from the differences in the ...
221 views

### How to figure out which words have the same meaning in two different languages?

Imagine two languages that have only these words: Man = 1, deer = 2, eat = 3, grass = 4 And you would form all sentences possible from these words: ...
120 views

### Is there any measure of separability of classes?

I want to know if there is a measure of how well two classes in Y are separable (linearly or not) based on their features in X. Easiest way of explaining this is to compare it to correlation ...
56 views

### How to calculate the false positives and negatives?

I have a huge amount of data and I want to calculate my false positive and false negative. Is there a software that can help me determine it?
553 views

### Does the correlation between inputs affect the model performance?

I'm currently working on a regression problem and I have 10 inputs/attributes. What should I do if there are correlations between different features of the input data? Does the correlation between ...
1 vote
83 views

### Auto-regression - Reduce error in prediction

I am trying to develop a time series model using autoregression. The data set is like as follows ...
1k views

### How does noise affect generalization?

Does increasing the noise in data help to improve the learning ability of a network? Does it make any difference or does it depend on the problem being solved? How is it affect the generalization ...
273 views

### Reinforcement learning objective as conditional expectations

In one of his lectures Levine describes the objective of reinforcement learning as: $$J(\tau) = E_{\tau\sim p_\theta(\tau)}[r(\tau)]$$ where $\tau$ refers to a single trajectory and $p_\theta(\tau)$ ...
1 vote