Questions tagged [statistical-ai]

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

Filter by
Sorted by
Tagged with
1
vote
0answers
7 views

Keras correlation coefficient as network metric in R

does anyone know how to use the correlation coefficient or squared correlation coefficient as a metric in keras in R (although other languages may provide clues). This is for a CNN that functions ...
3
votes
2answers
55 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?
4
votes
1answer
36 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 ...
-1
votes
1answer
36 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?
0
votes
0answers
28 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...
1
vote
1answer
16 views

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

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 ...
0
votes
0answers
16 views

Auto Regression Predicting large negative number

I am using Auto Regression for prediction Library: statsmodel Sample Python Code: ...
1
vote
1answer
38 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 ...
0
votes
0answers
16 views

How to interpret the generated ACF and PACF plot in time-series problem?

I recently started working onto Time-Series problem and gathered insights onto the working and the logic behind. However I'm still not clear that how ACF and PACF plots help us in building a model? ...
5
votes
2answers
627 views

Why exactly do neural networks require i.i.d. data?

In reinforcement learning, in general, successive states (actions and rewards) are highly correlated. An "experience replay" buffer was used, in the DQN architecture, to avoid training the neural ...
1
vote
2answers
55 views

Can we derive the distribution of a random variable based on a dependent random variable's distribution?

In the diagram below, there are three variables: X3 is a function of (depends on) X1 and X2, ...
5
votes
1answer
963 views

Are neural networks statistical models?

By reading the abstract of Neural Networks and Statistical Models paper it would seem that ANNs are statistical models. In contrast Machine Learning is not just glorified Statistics. I am looking ...
3
votes
1answer
105 views

Why KNN, Decision Trees, etc have a high variance?

Some examples of low-variance Machine Learning algorithms include Linear Regression, Linear Discriminant Analysis and Logistic Regression. Examples of high-variance Machine Learning algorithms ...
2
votes
3answers
148 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 ...
4
votes
1answer
103 views

Methodology bias in AI textbooks

Let me compare two textbooks: (1) "Artificial Intelligence: A Modern Approach" by Stuart J. Russell and Peter Norvig and (2) "Artificial Intelligence: Structures and Strategies for Complex Problem ...
5
votes
1answer
217 views

What are the differences in scope between statistical AI and classical AI?

What are the differences in scope between statistical AI and classical AI? Real-world examples would be appreciated.
3
votes
2answers
107 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 $p_\theta(\tau)$ ...
8
votes
1answer
1k views

Is Nassim Taleb right about AI not being able to accurately predict certain types of distributions?

So Taleb has two heuristics to generally describe data distributions. One is Mediocristan, which basically means things that are on a Gaussian distribution such as height and/or weight of people. The ...
1
vote
0answers
328 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 ...
1
vote
0answers
75 views

Confidence interval around a DNN prediction

I am facing a problem and do not know whether it is even solvable: I want to predict the behaviour of a system using a DNN, say a CNN, in the sense that I want to predict the time and intensity of a ...
2
votes
2answers
73 views

Finding the right questions to increase accuracy in classification

Lets say I have a list of 100k medical cases from my hospital, each row = patient with symptoms (such as fever , funny smell, pain etc.. ) and my labels are medical conditions such as Head trauma, ...
-1
votes
1answer
377 views

Are standard deviation, variance, skew good features for ML?

Pretty simple question here: Is it useful to use the standard deviation, skew, kurtosis, or any other extrapolatory stats as features, and if so in which problem sets? In this case, I am talking ...
13
votes
2answers
4k views

What is sample efficiency, and how can importance sampling be used to achieve it?

For instance, the title of this paper reads: "Sample Efficient Actor-Critic with Experience Replay". What is sample efficiency, and how can importance sampling be used to achieve it?
2
votes
1answer
71 views

Computing a “prominence score” (Computer Vision)

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 ...
3
votes
2answers
96 views

Figure out the meaning of words

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: ...
3
votes
1answer
135 views

With gradient descent w/MSE on a regression, must/should every Epoch use the exact same training samples?

Let's say I've got a training sample set of 1 million records, which I pull batches of 100 from to train a basic regression model using gradient descent and MSE as a loss function. Assume test and ...
5
votes
1answer
181 views

What is Statistical relational learning?

I have gone through the wikipedia explanation of SRL. But, it only confused me more: Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is ...
6
votes
4answers
655 views

What are some examples of statistical AI applied to real-world problems?

I believe that statistical AI uses inductive thought processes. For example, deducing a trend from a pattern, after training. What are some examples of successfully applied statistical AI to real-...
10
votes
3answers
504 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 ...