Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [inference]

30 questions
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how do I calculate p-value?

I need to calculate statistical significance of difference between two time series, each with 4500 terms. My null hypothesis is that $H_0: \mu=\mu_0$. How can I calculate p-value? Is Z-statistic useful for p value calculation? How to get p-value…
nick_name
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How do I make inference about test metrics for entire population from sample metrics?

Generally we calculate specific metrics for ML models on a test set (and we try to make that test set representative). I'm not clear on how to make inference about the same metrics for the population that the test set is representing - i.e., say I…
Shirish Kulhari
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p-value and effect size

Is it correct to say that the lower the p-value is the higher is the difference between the two means of the two groups in the t-test? For example, if I apply the t-test between two groups of measurements A and B and then to two groups of…
HelpNeederStudent
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Maximum number of classes YOLO net can recognize on mobile

I'm trying to make a mobile app on image recognition(Computer Vision Application) . Does anyone know whether modern day smartphones have enough processing power/memory to recognize, say about 1 million classes from their real-time camera feed (30…
R. Rudinthkin
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1 answer

In keras seq2seq model, what is the difference between `model.predict()` and the inference model?

I am looking into seq2seq model in keras, for example, this blog post from keras or this. All the examples I have seen have some inference model, that depicts the original model. That inference model is then used to make the predictions. My question…
BlueMango
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How train - test split works for Graph Neural Networks

I have recently started studying GNN's. I have covered GCN and GraphSage so far. But I am confused regarding the process when testing occurs. Now suppose in the graph above I am using the nodes as train and test set as shown in the figure. Suppose…
Sourajit
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2 answers

Combining CNNs for image classification

I would like to take the output of an intermediate layer of a CNN (layer G) and feed it to an intermediate layer of a wider CNN (layer H) to complete the inference. Challenge: The two layers G, H have different dimensions and thus it can't be done…
Andrew
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What is the best way to combine cross-validation and bootstrapping for one application?

We intend to model data with non-parametric covariate splines and we would like to understand the uncertainty of the parameter estimates/response estimates. Currently, we use cross-validation to model the optimal smoothness of our spline models…
Stan Tendijck
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1 answer

How can I deal with a computationally expensive simulator method in Sequential Monte Carlo/Approximate Bayesian Computation?

I am doing Approximate Bayesian Computation with Sequential Monte Carlo with PyMC in a way that is similar to what is described in this example of the PyMC documentation. The motivation for choosing this approach is that I have a simulator method…
lm1909
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1 answer

Inference Process in Autoregressive Transformer Architecture

I'm abit confused about how the inference/prediction process works in transformer. For simplicity suppose it is a transformer for translation. My understanding is that when training, the whole input and output sentences are put into model. This is…
Magic man Wryan Bang
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Whether to use LDA or QDA

I'm trying to determine whether it's best to use linear or quadratic discriminant analysis for an analysis that I'm working on. It's my understanding that one of the motivations for using QDA over LDA is that it deals better with circumstances in…
Peter
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Can I conduct independent t-test when data is infested with outliers ? and how to interpret the t-statistics?

I am working on 2 sample independent t-test. I have conducted analysis on test group vs control group and I have to write a report but I have few questions. Do we have to take out the outliers and then perform t-test? Once I perform t-test- can…
pinky
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Exogeneous, Endogenous Variables in Structural Causal Model

https://en.wikipedia.org/wiki/Causal_model#Definition Wikpedia defines causal models as: an ordered triple $\langle U, V, E\rangle$, where $U$ is a set of exogenous variables whose values are determined by factors outside the model; $V$ is a set of…
Eisen
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Causal Network Graph

I've been reading this blog (https://deepmind.com/blog/article/Causal_Bayesian_Networks) and am just getting into Causal inference. I have a question regarding causal network graphs. Let's say given data, how exactly are causal network graphs…
Eisen
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Model accuracy when training on GPU and then inferencing on CPU

When we are concerned about speed, GPU is way better than CPU. But if I train a model on a GPU and then deploy the same trained model (no quantization techniques used) on a CPU, will this affect the accuracy of my model? Can the accuracy of the same…
Devashish Prasad
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