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Questions tagged [variance]

4 votes
1 answer
71 views

I'm currently studying topics related to classical statistics and machine learning, and I’m trying to reconcile how the terms precision and accuracy are defined in both domains. Precision in classical ...
guest156789's user avatar
3 votes
0 answers
44 views

Say I have 3 time series. Index X, Sentiment Y, and Rate Z, all floats, x-axis is time. My hypothesis is, Index X is composed or influenced by both Y, Z plus some noise. How can I get an estimate for ...
Sebastian's user avatar
  • 131
1 vote
0 answers
16 views

I’m a fourth-year Applied Math student currently writing my diploma thesis on variance reduction in online experiments. My goal is to apply different variance reduction techniques (e.g., ...
Юлія Столярук's user avatar
3 votes
1 answer
169 views

Let's say there's an array containing float numbers, and it's size is n. Now m numbers will be chosen out of this array, and these m numbers' sum will generate a new number. So all these possible ...
Shane's user avatar
  • 143
-1 votes
1 answer
47 views

I have two sets of data: one is set1=[2,2,2,4.5] and set2=[2,1.5,2,4.5,2.5]. If I plot their distributions, set1 is: set2 is: I would say that set2 is a wider distribution and so I would expect a ...
LearningAlgorithm's user avatar
0 votes
0 answers
36 views

I am using simulations to compare two economic models and want to understand their impact on returns (i.e., the percentage change in prices). I have employed common random numbers for these ...
Apod's user avatar
  • 1
2 votes
1 answer
533 views

I'm new to Machine Learning and I understand bias and variance in theory but I can't seem to find a single source that explains how bias or variance can be computed. I'd like to do it in Python and ...
William's user avatar
  • 123
0 votes
1 answer
230 views

The purpose of weight initialization in the neural network is to keep the variance of calculation output in the layers to 1.0, and it depends on the calculations involved in the layers. Initializing ...
mon's user avatar
  • 829
0 votes
1 answer
568 views

I'm experimenting with the characterization of data over time. I generated some synthesized data with certain periodic patterns over time every 5mins (granularity of 5mins= data generated with the ...
Mario's user avatar
  • 610
0 votes
1 answer
92 views

This question is from a uni module about machine learning. I'm a bit stuck as I can't relate it to the bias-variance trade-off, to me the question implies all models have something to do with the ...
pixel.t87's user avatar
0 votes
1 answer
82 views

Why is this used to calculate a sample's standard deviation: $s=\sqrt{\frac{1}{N-1}\sum_{i=1}^N(x_i-\bar{x})^2}$ and not something like: $s=\frac{1}{N-1}\sqrt{\sum_{i=1}^N(x_i-\bar{x})^2}$ I ...
Daniel Jiang's user avatar
0 votes
1 answer
290 views

I was going through bias and variance tradeoff article and it makes use of bias_variance_decomp function from mlxtend library. ...
Mahesha999's user avatar
1 vote
1 answer
78 views

This is a question for beginners. edited 19/11. I am really confused by the term variance and so many other variants. For example, the figure below shows the variance of two models to compare. Is ...
asaddummie's user avatar
0 votes
1 answer
256 views

I am having a hard time understanding how to compare results of MSE and variance of data to eachother. I understand that MSE is used to calculate how far off data points are from a prediction, say you ...
Kodak's user avatar
  • 1

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